WO2019205791A1 - Method and device for adjusting data plan for a plurlaity of user identifications - Google Patents

Abstract

The present application discloses a method and device for adjusting data plan for a plurality of user identifications, belonging to the communication technology field. The plurality of user identifications share a data volume in a data plan provided by an operator; the method comprises: acquiring a data plan and a data consumption record of each of the plurality of user identifications before the current time point of a billing cycle; predicting the sum of the consumed data of the plurality of user identifications in the billing cycle according to the data consumption records, so as to obtain a predicted total consumed data; sending data plan adjusting indication information comprising at least one user identification of the plurality of user identifications and a corresponding new data plan to a billing system of the operator according to the predicted total consumed data and the data plan of each user identification, so as to indicate the billing system to adjust a data plan for the at least one user identification. In such a way, the data plan of the current billing cycle can be automatically adjusted and the adjusting mode is more timely and accurate.

Description

Method and device for adjusting traffic packages for multiple user identifications

This application claims the priority of the Chinese patent application filed on April 28, 2018, the Chinese National Intellectual Property Office, the application number is 201810403353.4, and the invention name is "method and device for adjusting the flow package for multiple user identifications". This is incorporated herein by reference.

Technical field

The present application relates to the field of communications technologies, and in particular, to a method and apparatus for adjusting a traffic package for multiple user identifiers.

Background technique

In the field of communication technology, many devices need to perform traffic services such as communication or Internet access based on the user identity provided by the operator. The user identifier is used by the operator to identify the identity of the user. In actual application, the user identifier may be a Subscriber Identification Module (SIM) card, a User Identity Module (UIM) card, or the Internet of Things. The identifier of the network card such as a card may also be a user equipment identifier or a user account. Moreover, in practical applications, the operator can provide package traffic for each user identity according to the traffic plan ordered by each user identity, for the user to identify. The traffic package of each user identifier may include the amount of traffic in the package included in the charging period of the user identifier, the unit price of the in-package, and the unit price of the out-of-package. The billing period refers to the billing period of the operator. For example, you can use the natural month as the billing cycle.

Currently, in many application scenarios, multiple user identifiers can share the amount of traffic in the in-package provided by the operator, that is, the number of in-package traffic provided by the operator for the multiple user identifiers can be aggregated and used together. The user ID with a large actual traffic consumption can use the in-package traffic of the user ID with a large traffic balance in the package. When the settlement is performed at the end of the billing period, the user may perform settlement according to the total actual consumption traffic of the plurality of user identifiers in the billing period according to the plurality of user identifiers pre-ordered traffic packages: The portion of the total in-package traffic volume of the plurality of user identifiers is settled according to the unit price of the traffic within the package, and the portion exceeding the traffic volume of the total package is settled according to the unit price of the package. Since the unit price of the traffic outside the package is often much higher than the unit price of the package traffic, it is necessary to adjust the traffic package of the user identification according to the cost.

In the related art, after a billing period of one billing cycle, the data bill of the next billing period is determined according to the settlement result of the billing period, so that the billing fee of the next billing period is minimized. This may be a problem in that the package adjustment is not timely (it must wait until the next billing cycle to adjust), and the inaccuracy (the amount of traffic in the adjusted package is too much or too little compared with the actual consumption flow).

Summary of the invention

In order to solve the problem that the adjustment of the traffic package is not timely and inaccurate in the related art, the present application provides a method and device for adjusting a traffic package for multiple user identifiers. The technical solution is as follows:

In a first aspect, a method for adjusting a traffic package for multiple user identifiers is provided, where the multiple user identifiers share a number of in-package flows provided by an operator, and the method includes:

Obtaining a data package and a traffic consumption record corresponding to each user identifier of the multiple user identifiers before the current time point of the charging period;

Determining, according to the traffic consumption record, a sum of consumption flows of the multiple user identifiers in the charging period, and obtaining a predicted total consumption traffic;

And sending the traffic plan adjustment indication information to the charging system of the operator according to the predicted total consumption traffic and the traffic plan corresponding to each user identifier of the multiple user identifiers, to indicate that the charging system is At least one of the plurality of user identifiers adjusts the traffic plan, so that the settlement fee of the plurality of user identifiers that are settled with the operator according to the adjusted traffic plan in the billing period is less than the traffic according to the adjustment a settlement fee for settlement of the package with the operator, wherein the data package adjustment indication information includes at least one of the plurality of user identifiers and a corresponding new traffic package.

In the embodiment of the present application, the traffic package and the traffic consumption record corresponding to each user identifier in the multiple user identifiers before the current time point of the charging period may be obtained at any time in the charging period, and then according to the current time point. a traffic consumption record of each user identifier in the user identifier, predicting a sum of consumption flows of the plurality of user identifiers in a billing period, and obtaining a predicted total consumption traffic, according to the predicted total consumption traffic and each user identifier corresponding to the The traffic plan sends the traffic plan adjustment indication information to the charging system of the operator, where the data package adjustment indication information includes at least one user identifier and a corresponding new traffic package of the multiple user identifiers, to indicate that the charging system is The at least one user identifier adjusts the traffic plan to reduce the settlement fee of the plurality of user identifiers and the operator. That is, the total consumption traffic of the plurality of user identifiers in the billing period can be accurately predicted at any time within the billing period, and the traffic plan of the plurality of user identifiers is automatically performed according to the predicted total consumption traffic. The adjustment makes the settlement fee of the current billing cycle minimize. Compared with the artificial adjustment method in the related art, the adjustment method is more timely and more accurate, and the user can further save the settlement fee, and the flexibility is high.

In a specific implementation, the sending the data package adjustment indication information to the charging system of the operator according to the predicted total consumption traffic and the data package corresponding to each user identifier of the multiple user identifiers includes:

And accumulating the amount of the in-package traffic in the data package corresponding to each of the plurality of user identifiers, to obtain the total package traffic;

Determining a first difference between the predicted total consumption flow and the total package flow;

And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator.

That is, the predicted total consumption traffic of the plurality of user identifiers and the total package traffic may be compared, and then the traffic packages of the plurality of user identifiers are adjusted according to the comparison result, and the accuracy is high.

In a specific implementation, the traffic packages corresponding to the multiple user identifiers are the same;

And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator, including:

Determining a second between the predicted total consumption traffic and the quantity of the at least one user identifier when the first difference is greater than or equal to a preset threshold and the at least one user identifier is the plurality of user identifiers ratio;

Determining, between the plurality of service packages provided by the operator, a quantity between the number of flows in the package and the second ratio, according to the second ratio The traffic plan with the smallest difference is used as the new traffic package of the user identifier A, or from the plurality of traffic packages, determining that the amount of traffic in the package is greater than or equal to the second ratio and between the second ratio The traffic plan with the smallest difference is used as the traffic package of the user identifier A, or from the plurality of traffic packages, determining that the total consumption traffic of the user identifier A in the billing period is equal to the first In the case of the second ratio, the traffic plan with the lowest settlement tariff of the operator is used as the new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

In the embodiment of the present invention, when the traffic packages of the plurality of user identifiers are the same and the at least one user identifier is the multiple user identifiers, according to the predicted total consumption traffic and the quantity of the at least one user identifier The second ratio between the two adjusts the current traffic plan of the at least one user identity. That is, the traffic package of the multiple user identifiers may be adjusted according to the average consumption traffic of each of the multiple user identifiers in the fee period, so that each of the multiple user identifiers may be implemented according to the The average traffic consumption of the user ID is adjusted uniformly for each user-identified traffic package. This adjustment method can reduce the calculation amount and improve the adjustment efficiency. In a specific implementation, the traffic packages corresponding to the multiple user identifiers are different;

And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator, including:

Determining, when the first difference is greater than or equal to a preset threshold, and the at least one user identifier is the plurality of user identifiers, determining a first ratio between the predicted total consumption traffic and the total package traffic;

Determining, by any one of the at least one user identifiers A, a product of the number of in-package traffic in the traffic plan corresponding to the user identifier A and the first ratio;

According to the product, a traffic plan with the smallest difference between the number of traffic in the package and the product is determined as the traffic package of the user identifier A, or from the plurality of traffic packages provided by the operator. In the plurality of traffic packages, determining, by the traffic plan that the number of traffic in the package is greater than or equal to the product, and the difference between the products is the traffic package of the user identifier A, or from the multiple traffic In the package, determining, as the user identifier A, a traffic plan with the minimum settlement tariff between the user identifier A and the operator in the case where the total consumption flow in the billing period is equal to the product Data Package;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

In the embodiment of the present invention, when the traffic packages of the plurality of user identifiers are different and the at least one user identifier is the multiple user identifiers, the first ratio between the predicted total consumption traffic and the total package traffic may be adjusted. The current traffic package of the at least one user identity. That is, the traffic package of the plurality of user identifiers may be adjusted according to a ratio between the predicted total consumption traffic and the total package traffic, so that the overall traffic consumption according to the multiple user identifiers may be implemented, for each The traffic metrics of the user IDs are adjusted in equal proportions with high accuracy.

In a specific implementation, the sending the data package adjustment indication information to the charging system of the operator according to the first difference, including:

Determining, when the first difference is greater than or equal to a preset threshold, a third ratio between the first difference and the number of the at least one user identifier;

When the predicted total consumption traffic is less than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic plan corresponding to the user identifier A, and the number a second difference between the three ratios;

Determining, according to the second difference, a traffic plan with the smallest difference between the number of flows in the package and the second difference from the plurality of data packages provided by the operator as the user identifier A a new traffic package, or a traffic plan from the plurality of traffic packages that determines that the amount of traffic in the package is greater than or equal to the second difference and the difference between the second difference is the smallest Identifying a new traffic package of A, or determining, from the plurality of traffic packages, that the total consumption flow of the user identifier A in the charging period is equal to the second difference, and the operation The traffic plan with the lowest settlement tariff between the merchants is used as the new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

In a specific implementation, after determining the third ratio between the first difference and the quantity of the at least one user identifier, the method further includes:

When the predicted total consumption traffic is greater than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic package corresponding to the user identifier A, and the number The sum between the three ratios;

Determining, according to the sum of the plurality of data packages provided by the operator, a traffic package having the smallest difference between the number of traffic in the package and the sum value as the new traffic package of the user identifier A, Or determining, from the plurality of data packages, a traffic package whose amount of traffic in the package is greater than or equal to the sum value and having a smallest difference from the sum, as a new traffic package of the user identifier A, or And determining, in the plurality of traffic packages, a traffic plan having a minimum settlement tariff with the operator when the total consumption flow of the user identifier A in the charging period is equal to the sum value The new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

In the embodiment of the present invention, at least one user identifier may be selected from the plurality of user identifiers, and the traffic package of the at least one user identifier is adjusted on average according to the first difference. This adjustment method does not need to adjust the traffic package of each user identifier, which reduces the calculation amount and improves the adjustment efficiency.

In the embodiment of the present application, a plurality of specific traffic package adjustment manners are provided, which can meet the diversity requirements of users and improve the user experience.

In a specific implementation, the predicting the total consumption traffic of the multiple user identifiers in the charging period according to the traffic consumption record, and obtaining the predicted total consumption traffic, including:

Performing statistics on the traffic consumption record to obtain actual consumption traffic of the multiple user identifiers in at least one first time interval, where the at least one first time interval refers to the first time from the charging period At least one time interval from the interval to the target time interval;

Wherein, when the current time point is the end time of a time interval in the charging period, the target time interval is a time interval in which the current time point is located, and when the current time point is not a time interval in the charging period The end time interval is the latest time interval before the current time point in the billing period;

Determining, according to actual consumption flows of the plurality of user identifiers in the at least one first time interval, predicted consumption flows of the plurality of user identifiers in at least one second time interval, the at least one second time interval Means at least one time interval after the target time interval in the billing period;

Adding the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval and the predicted consumption flow rate in the at least one second time interval to obtain the predicted total consumption flow rate.

In the embodiment of the present application, by counting the actual consumption flows before the current time point in units of time intervals of the charging period, and predicting the predicted consumption flow after the current time point, the statistics and prediction processing can be improved. Efficiency, as well as the accuracy of statistics and forecasts.

In a specific implementation, the determining, according to the actual consumption traffic of the multiple user identifiers in the at least one first time interval, determining predicted consumption flows of the multiple user identifiers in the at least one second time interval, including :

Determining, according to the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval, a predicted consumption of the plurality of user identifiers in the at least one second time interval by a preset moving average model method flow.

Among them, the sliding average model method refers to a method of predicting the data value of the next period or period by using a set of recent actual data values. The basic idea is to sequentially calculate the order of a certain number of items according to the time series data. Time average to reflect long-term trends. In the embodiment of the present application, the preset sliding average model method can accurately predict the traffic consumption trend of the multiple user identifiers in the future time interval, and can eliminate the effects of periodic fluctuations and random fluctuations, and the prediction accuracy is better. high.

In a specific implementation, the determining, by the preset moving average model method, the plurality of user identifiers in the at least one part according to the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval Forecasted consumption flows over the two time intervals, including:

For any of the at least one second time interval B, when the second time interval B is one of the first N time intervals within the charging period, and the plurality of time intervals When the user ID does not have a data traffic consumption record in the previous billing period of the billing period, the average of the target consumption flows in all time intervals before the second time interval B in the billing period a value, determined as the predicted consumption flow rate of the plurality of users in the second time interval B;

When the second time interval B is one time interval of the first N time intervals in the charging period, and the multiple user identifiers have data traffic in a previous charging period of the charging period When the record is consumed, or when the second time interval B is any time interval after the Nth time interval in the charge period, the target of the N time intervals before the second time interval B The average of the consumption flows is determined as the predicted consumption flow of the plurality of users in the second time interval B:

Wherein, the N is a positive integer, and for any time interval C before the second time interval B, when the plurality of user identifiers have actual consumption flows in the time interval C, the time interval The target consumption flow rate of C refers to the actual consumption flow rate of the plurality of user identifiers in the time interval C, and when the plurality of user identifiers do not have actual consumption flow rate in the time interval C, the time interval The target consumption flow rate of C refers to the predicted consumption flow rate of the plurality of user identifiers in the time interval C.

When the second time interval B is one of the first N time intervals in the charging period, and the plurality of user identifiers do not have the actual consumption flow record in the previous charging period of the charging period, Directly calculating an average value of target consumption flows of all time intervals before the second time interval B in the billing period, and determining the average value as the predicted consumption flow rate of the plurality of user identifiers in the second time interval B If the time interval of the consumption flow record is less than N before the second time interval B, the predicted consumption average flow rate in the second time interval B can also be predicted by using the preset moving average model method.

When the second time interval B is one of the first N time intervals in the charging period, and the plurality of user identifiers have actual consumption flow records in the previous charging period of the charging period, The average value of the target consumption flows of the N time intervals before the second time interval B is determined as the predicted consumption flow of the plurality of user identifiers in the second time interval B, which may be from the previous one of the charging periods Obtain the actual consumption flow of the last M time intervals in the actual traffic consumption record of the billing cycle, as the target consumption flow of the M time intervals, and compare the M intervals to the time before the second time interval B in the charging period. The interval is supplemented to obtain the target consumption flow of N time intervals, which improves the accuracy of the prediction.

In a specific implementation, the multiple user identifiers are identifiers of multiple Internet of Things cards that are bound to the target traffic pool and activated during the billing period, and the target traffic pool refers to any of the Internet of Things management. Traffic pool.

That is, the method provided by the embodiment of the present application can also be applied to the Internet of Things, and the Internet of Things can adjust the traffic package of multiple Internet of Things cards bound to the traffic pool through the traffic pool.

In a second aspect, there is provided an apparatus for adjusting a traffic plan for a plurality of user identities, the apparatus having a function of implementing a method behavior of adjusting a traffic plan for a plurality of user identities in the first aspect. The device includes at least one module, and the at least one module is configured to implement the method for adjusting a traffic package for multiple user identifiers provided by the foregoing first aspect.

A third aspect provides an apparatus for adjusting a traffic package for a plurality of user identifiers, where the apparatus includes a processor and a memory, and the memory is configured to store a support traffic plan adjustment apparatus to perform the foregoing first aspect. A program for identifying a method of adjusting a traffic plan for a plurality of users, and storing data related to a method for implementing a method of adjusting a traffic plan for a plurality of user IDs provided by the first aspect described above. The processor is configured to execute a program stored in the memory. The operating device of the storage device may further include a communication bus for establishing a connection between the processor and the memory.

In a fourth aspect, a computer readable storage medium is provided, wherein the computer readable storage medium stores instructions that, when run on a computer, cause the computer to perform the adjustment of the plurality of user identities as described in the first aspect above The method of the data package.

In a fifth aspect, a computer program product comprising instructions for causing a computer to perform the method of adjusting a traffic plan for a plurality of user identities as described in the first aspect above is provided when operating on a computer.

In a sixth aspect, a chip is provided, the chip comprising programmable logic circuits and/or program instructions, and the method for adjusting a traffic package for multiple user identifiers according to the first aspect described above when the chip is running .

The technical effects obtained by the second aspect, the third aspect, the fourth aspect, the fifth aspect, and the sixth aspect are similar to those obtained by the corresponding technical means in the first aspect, and are not described herein again.

The beneficial effects brought by the technical solutions provided by the present application are:

In the embodiment of the present application, the traffic package and the traffic consumption record corresponding to each user identifier in the multiple user identifiers before the current time point of the charging period may be obtained at any time in the charging period, and then according to the current time point. a traffic consumption record of each user identifier in the user identifier, predicting a sum of consumption flows of the plurality of user identifiers in a billing period, and obtaining a predicted total consumption traffic, according to the predicted total consumption traffic and each user identifier corresponding to the The traffic plan sends the traffic plan adjustment indication information to the charging system of the operator, where the data package adjustment indication information includes at least one user identifier and a corresponding new traffic package of the multiple user identifiers, to indicate that the charging system is The at least one user identifier adjusts the traffic plan to reduce the settlement fee of the plurality of user identifiers and the operator. That is, the total consumption traffic of the plurality of user identifiers in the billing period can be accurately predicted at any time within the billing period, and the traffic plan of the plurality of user identifiers is automatically performed according to the predicted total consumption traffic. The adjustment makes the settlement fee of the current billing cycle minimize. Compared with the artificial adjustment method in the related art, the adjustment method is more timely and more accurate, and the user can further save the settlement fee, and the flexibility is high.

DRAWINGS

1 is a system architecture diagram of a traffic package adjustment system according to an embodiment of the present application;

2 is a system architecture diagram of an Internet of Things service system provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of an operation manner between an Internet of Things service provider 50 and an operator 10 according to an embodiment of the present application;

4 is a schematic diagram of a logical structure of an Internet of Things application provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a device for adjusting a traffic package according to an embodiment of the present application;

6 is a flowchart of a method for adjusting a traffic package for multiple user identifiers according to an embodiment of the present application;

FIG. 7 is a timing diagram of operations of a target traffic pool according to an embodiment of the present application;

FIG. 8 is a schematic structural diagram of an apparatus for adjusting a traffic package for multiple user identifiers according to an embodiment of the present application.

detailed description

In order to make the objects, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

Before the detailed explanation of the application, the application scenario of the present application is introduced.

The method for adjusting the traffic plan adjustment for multiple user identifiers provided by the embodiment of the present application is mainly applied to the scenario in which the plurality of user identifiers share the amount of traffic in the package provided by the operator. The user identifier in the embodiment of the present application is used by the operator to identify the identity of the user, so that the operator can provide the mobile communication access service for the device according to the user identifier. In an actual application, the user identifier may be an identifier of a network card such as a SIM card, a UIM card, or an Internet of Things card, or may be an identifier of a user equipment or a user account.

The traffic package of each user identifier includes the number of traffic in the package, the package price, and the unit price of the package. The amount of traffic in the package refers to the total amount of traffic that the operator can provide for the user identity according to the traffic package. In an actual application, the amount of traffic in the package includes the amount of traffic that the user identifier purchases from the service provider through the traffic package, and further includes the traffic that the operator identifies to the user according to the actual amount of traffic consumed by the user identifier. Quantity.

For example, taking the identifier of the multiple user identifiers as the SIM card as an example, the enterprise can purchase multiple SIM cards from the operator, order a traffic package for each SIM card according to actual needs, and agree with the operator to stipulate the multiple cards. The SIM card shares the amount of traffic in the package provided by the operator, and then distributes the multiple SIM cards to the enterprise employees, so that each enterprise employee can share the amount of traffic in the package using the multiple SIM cards, and the actual traffic consumption Larger users can use the in-package traffic of users with more traffic balances in the package.

For example, taking the multiple user identifiers as an Internet of Things card as an example, the method can be applied to a scenario in which a plurality of Internet of Things cards in the Internet of Things share the amount of traffic in the package provided by the operator.

Among them, the Internet of Things refers to the Internet of Things connected by objects. In practical applications, the Internet of Things can be an Internet of Things centered on transportation, logistics, medical care, and electric power. In practical applications, the Internet of Things, which is concentrated in the fields of transportation or logistics, can also be called the Internet of Vehicles. Vehicle networking refers to the use of advanced sensor technology, network technology, computing technology, control technology, and intelligent technology to comprehensively perceive roads and traffic, realize large-scale and large-capacity data interaction between multiple systems, and conduct traffic for each vehicle. Control, full-time control of traffic on each road, to provide traffic efficiency and traffic safety-based networks and applications, to provide technical support for the driver's safe driving and assisted driving.

It should be noted that most IoT direct service providers are not operators, but specialized IoT service providers, and IoT service providers need to use the carrier's communication services to provide services for IoT devices. In practical applications, the IoT service provider needs to obtain the IoT card from the operator, and use the specific traffic package to uniformly order the traffic to the operator, and then provide the ordered traffic to these IoT cards, and then use the payment after the first use. The method is to settle with the operator according to the actual traffic used by the IoT card and the pre-ordered traffic package.

Further, the plurality of Internet of Things cards may be an IoT card that is bound to and activated by any traffic pool managed by the Internet of Things, so that the traffic flow given by the operator is shared by the bound traffic pool.

In practical applications, the Internet of Things can usually manage one or more traffic pools and can operate and settle with carriers through the traffic pool. Each traffic pool is bound to at least one IoT card. The traffic pool refers to a virtual space that can aggregate the package traffic of at least one IoT card that is bound, and then share the used IoT card. Moreover, for any of the traffic pools, that is, the target traffic pool, the traffic packages of at least one IoT card bound to the target traffic pool may be the same or different.

In actual use, the Internet of Things can add the package traffic of the activated IoT card to the target traffic pool, and each activated IoT card can use the target traffic pool according to actual needs. The package traffic, when the usage time reaches the operator's settlement time, can be settled with the operator according to the pre-ordered traffic package according to the total traffic consumption of the target traffic pool in the billing cycle. The settlement includes two parts: the part of the total amount of the in-package flow that does not exceed the target traffic pool is settled according to the unit price of the flow within the package, and the part of the total amount of the flow within the total package is settled according to the unit price of the package.

In the embodiment of the present application, in order to ensure that the traffic packages of the multiple user identifiers in the charging period can satisfy the actual consumption traffic of the multiple user identifiers to a large extent, the multiple user identifiers are saved in the maximum amount. During the period of settlement of the tariff, a traffic consumption record of each of the plurality of user identifiers before the current time point in the charging period is predicted at any time within the charging period, and the plurality of user identifiers are predicted. The sum of the consumption flows in the billing period, the predicted total consumption traffic is obtained, and then the billing to the operator is based on the predicted total consumption traffic of the plurality of user identifiers in the billing period and the traffic plan corresponding to each user identifier. The system sends the traffic plan adjustment indication information to indicate a method for adjusting the traffic plan for at least one of the multiple user identifiers.

Next, the system architecture of the traffic package adjustment system according to the embodiment of the present application is introduced.

1 is a system architecture diagram of a traffic package adjustment system according to an embodiment of the present application. As shown in FIG. 1 , the system includes an operator 10, multiple user identifiers 20, multiple user devices 30, and a traffic plan adjustment device 40. .

The operator 10 is configured to provide traffic for each user identifier 20 according to the traffic plan of each user identifier 20, which may be any telecom carrier. Moreover, the operator 10 includes a billing system that can provide a billing fee service and a traffic plan management service for the user ID 20.

The plurality of user equipments 30 are in one-to-one correspondence with the plurality of user identifiers 20, and are configured to perform traffic services according to the corresponding user identifiers 20, and consume corresponding traffic of the user identifiers 20 in the process of performing traffic services. . It should be noted that FIG. 1 is only an example in which one user equipment 30 corresponds to one user identifier 20, and in actual application, one user equipment 30 may also correspond to multiple user identifiers 20, for example, one user equipment 30 may be installed. The network card is not limited in this embodiment.

The traffic package adjustment device 40 is configured to determine, according to the traffic package and the traffic consumption record of the multiple user identifiers 20, whether the traffic package of the multiple user identifiers 20 needs to be adjusted, and when it is determined that adjustment is needed, the traffic planner may be notified to the operator. The charging system of 10 sends the traffic plan adjustment indication information to instruct the charging system to adjust the traffic package for at least one of the plurality of user identifiers 20. The traffic plan adjustment indication information includes at least one user identifier to be adjusted and a corresponding new traffic package among the plurality of user identifiers determined by the traffic package adjustment device 40. Specifically, the traffic plan adjustment device 40 can transmit the traffic plan adjustment indication information to the charging system of the operator 10 through the interface with the operator 10. In an actual application, the traffic plan adjusting device 40 may be a management platform of the plurality of user identifiers 20, such as an Internet of Things management platform.

The plurality of user identifiers 20 can share the package traffic provided by the operator. In actual applications, the traffic packages of the multiple user identifiers 20 may be the same or different. For example, the plurality of user identifiers 20 can be pre-ordered with the same traffic package: 50 yuan per month for 1G traffic, exceeding 1G portion for 1 yuan/M. Assuming that the number of the plurality of user identifiers 20 is 1000, and the total traffic used by the plurality of user identifiers 20 in the current month is 1100 G, the settlement fee of the plurality of user identifiers 20 in the current month is 1000*50+100*1024* 1 = 152,400 yuan.

As can be seen from the above, in actual applications, the unit price of the traffic beyond the package is often much higher than the unit price of the traffic within the package. When the traffic package ordered in advance for the plurality of user identifiers 20 does not meet the actual traffic usage of the multiple network cards, In the case of circumstances, the settlement fee may be higher, so in order to save the settlement tariff, it is necessary to adjust the traffic package of the target traffic pool. In the related art, the traffic plan of the multiple user identifiers 20 needs to be manually adjusted, the adjustment efficiency and the accuracy are low, and the traffic plan of the next billing cycle can only be adjusted according to the settlement result of the current billing period. The adjustment is not timely and the settlement tariff cannot be saved to the maximum extent.

In the embodiment of the present application, a method is disclosed that predicts the total consumption traffic of the multiple user identifiers 20 in a billing period at any time within a billing period, and obtains a predicted total consumption flow, and according to the total forecast The method for automatically adjusting the traffic package of the plurality of user identifiers 20 by the consumption flow is more accurate and timely.

Further, the traffic package adjustment system can be applied to the Internet of Things. Next, the system architecture of the Internet of Things service system involved in the embodiment of the present application is introduced.

2 is a system architecture diagram of an Internet of Things service system provided by an embodiment of the present application. As shown in FIG. 2, the Internet of Things service system includes an operator 10, an Internet of Things service provider 50, and an Internet of Things device 60.

The operator 10 is configured to provide communication services for the Internet of Things service provider 50, and specifically provides the communication service for the Internet of Things service provider 50 through the Internet of Things card, and the operator 10 has a charging system capable of providing traffic for the Internet of Things device 60. Billing service and traffic plan management service. The Internet of Things Provider 50 is used to construct the Internet of Things by means of communication services provided by the operator 10, thereby providing services to the Internet of Things device 60 through the Internet of Things. The Internet of Things device 60 refers to a user device in the Internet of Things. For example, when the Internet of Things is a car network, the Internet of Things device 60 can be a vehicle in a car network.

In practical applications, the Internet of Things service provider 50 can integrate basic hardware products such as embedded systems, sensors, and communication modules, and on the other hand, system software, database software, application software, and device-to-device (Machine to Machine, M2M) Integrated services such as communication are integrated, and then combined with their own industry knowledge to form the final IoT application service and IoT terminal, and provide services for IoT users through various sales channels.

Specifically, the Internet of Things service provider 50 can integrate the M2M communication service of the operator 10 into the Internet of Things application service to form a Business to Business to Business (B2B2B) or a Business to Business to Business (Business to Business to Customer, B2B2C) business model. Among them, the business model of B2B2B means that the Internet of Things service provider 50 provides business-oriented business models for enterprise customers. The business model of B2B2C refers to the business model of the Internet of Things service providers 50 providing enterprises with end-users. The change of business model puts forward new requirements for operators 10 in IoT card management, resource management, product sales, after-sales support, and billing model. Under the new business model, operators should not only serve as communication channels, but also We should weaken barriers between industries, provide services based on traditional communication capabilities, IoT information, open and shared services, and provide customers with various forms of control and early warning capabilities and self-service capabilities under the conditions of supporting capabilities of the underlying network. In terms of service billing, it also supports a wider variety of billing methods, such as the way in which the Internet of Things and the Internet of Things service provider 20 operate and settle through the traffic pool.

Further, the Internet of Things Provider 50 can manage one or more traffic pools and can operate and settle with the operator 10 through a traffic pool. For example, in the related art, see 3, the operation mode between the Internet of Things service provider 50 and the operator 10 can be as shown in the following steps 101-103:

Step 101: After the Internet of Things service provider 50 obtains a batch of the Internet of Things card from the operator 10, the batch of the Internet of Things card is bound to the target traffic pool, and the batch of the Internet of Things card is inserted into the Internet of Things device 60 to provide The networked device 60 is used. The traffic packages of the batch of IoT cards that are bound to the target traffic pool may be the same or different. For example, the batch of IoT cards can have the same traffic package: 50 yuan per month for 1G traffic, exceeding 1G for 1G/M.

Step 102: The Internet of Things service provider 50 and the operator 10 generally operate and settle through the traffic pool. That is, the Internet of Things service provider 50 can set the package traffic of each IoT card in the batch of Internet of Things cards. It is added to the target traffic pool for use by the IoT device 60 where the batch of IoT cards are located, and the portion of the package traffic that exceeds the target traffic pool will be settled according to the unit price of the off-package traffic.

For example, if there are 1000 IoT cards and the 1000 IoT cards are correspondingly inserted into 1000 IoT devices 60, the IoT service provider 50 can add the package traffic of the 1000 IoT cards to In the target traffic pool, the 1000 IoT devices 60 are used together. Assume that each IoT card's traffic package is 50 yuan per month for 1G traffic, which exceeds 1G for 1 yuan/M. The target traffic pool's monthly package traffic total is 1000*1G=1000G, which can be used for 1000G. 1000 IoT devices 60 are used together, and portions that use more than 1000G will be charged at 1 yuan/M.

Step 103: The Internet of Things service provider 50 and the operator 10 use the method of first use post-payment to settle, and all charges in the billing period are settled at the settlement time of each billing period. For example, based on the above example, assuming that the total traffic used by the 1000 Internet of Things devices 60 in the current month is 1100G, the settlement fee for the current month is 1000*50+100*1024*1=152400 yuan.

Further, the Internet of Things Provider 50 can provide IoT users with IoT applications and operate and manage IoT cards and IoT devices through IoT applications. For example, in the embodiment of the present application, the consumption flow of any managed traffic pool may be predicted by the Internet of Things application, and the traffic plan adjustment indication information is sent to the charging system of the operator 10 according to the prediction result, to indicate the The fee system adjusts the traffic plan for the IoT card that is bound to the traffic pool.

For example, in the case where the Internet of Things service provider 50 provides services to enterprise customers through the Internet of Things application, the enterprise customer can also manage the Internet of Things card or the Internet of Things device, select the traffic for the Internet of Things card or the traffic pool through the Internet of Things application. The package, the diagnosis of the Internet of Things device, and the viewing of bills and reports, and of course, can also provide other services for the enterprise customers, which is not limited in the embodiment of the present application.

4 is a schematic diagram of a logical structure of an Internet of Things application provided by an embodiment of the present application. As shown in FIG. 4, the Internet of Things application includes an application (Usage) module 411, a network card management module 412, and a traffic pool (Volume Pool) statistical analysis. Module 413.

The Usage module 411 is responsible for the flow rate and control of the IoT card, and the traffic consumption record of the IoT card can be obtained from the operator 10, for example, the traffic of the IoT card is obtained from the operator 10 through the installed operator access integration. The consumer record integration, the operator access integration is the interface between the IoT application and the operator 10. In the embodiment of the present application, the application module 411 can also send the traffic consumption record of the Internet of Things card to the traffic pool statistical analysis module 413. In an actual application, the application module 411 can send the traffic consumption record of the IoT card to the traffic pool statistics analysis module 413 through the Kafka message, and can also be sent by other means. Among them, Kafka is a high-throughput distributed publish and subscribe message system that can process all action flow data in a consumer-scale website. The traffic consumption record of the IoT card can be the CDR file of the IoT card.

The network card management module 412 is responsible for managing the traffic pool included in the Internet of Things application and the IoT card bound to each traffic pool, and specifically acquiring and storing the information of each traffic pool, the IoT card information bound to each traffic pool, Information such as the traffic plan of each traffic pool and the status change information of the IoT card bound to each traffic pool. In the embodiment of the present application, the network card management module 412 may also change the status of each traffic pool information, the Internet of Things card information bound to each traffic pool, the traffic package of each traffic pool, and the IoT card bound to each traffic pool. The information and the like are sent to the traffic pool statistical analysis module 413. In an actual application, the network card management module 412 can send the foregoing information to the traffic pool statistics analysis module 413 by using a kafka message.

Specifically, referring to FIG. 4, the network card management module 412 may include a traffic pool import unit and a traffic pool management unit, where the traffic pool import unit is configured to determine an Internet of Things card acquired by the Internet of Things service provider, and the traffic pool management unit is configured to determine the object. Networked applications include traffic pools and IoT cards that are bound to individual traffic pools, and can manage individual traffic pools and IoT cards that are bound to individual traffic pools.

The traffic pool statistics analysis module 413 is configured to determine, according to information acquired from the application module 411 and the network card management module 412, a plurality of Internet of Things cards activated by the target traffic pool before the current time point in the charging period, and the statistics are performed. The traffic consumption record of the plurality of IoT cards before the current time point in the current period, and then predicting the sum of the consumption flows of the plurality of IoT cards in the billing period according to the statistical result, obtaining the predicted total consumption flow, and accumulating the total The amount of traffic in the package in the traffic package corresponding to each IoT card of the plurality of Internet of Things cards, and the total package traffic is obtained, so as to predict the total consumption traffic and the total package according to the plurality of IoT cards in the charging cycle. The traffic is determined whether the traffic package of the plurality of Internet of Things cards needs to be adjusted.

Specifically, the traffic pool statistics analysis module 413 may include a data synchronization unit, a card activation number statistics unit, a gift flow accumulation unit, a consumption flow accumulation unit, a traffic prediction unit, and an automatic adjustment unit. The data synchronization unit is configured to synchronize data from the application module 411 or the network card management module 412, that is, receive data sent by the application module 411 or the network card management module 412. The card activation number statistics unit is configured to perform statistics on the activation number of the IoT card bound to the target traffic pool according to the state change information of the IoT card bound to the target traffic pool sent by the network card management module 412. The consumption flow accumulating unit is configured to accumulate the traffic consumed by the target traffic pool according to the traffic consumption record of the IoT card sent by the application module 411. The traffic prediction unit is configured to predict the total consumption traffic of the target traffic pool in the charging period according to the actual consumption traffic of the target traffic pool before the current time point in the charging period, and obtain the predicted total consumption traffic. The gift flow accumulation unit is configured to accumulate the package traffic of the target traffic pool according to the traffic package of the target traffic pool sent by the network card management module 412. The automatic adjustment unit is configured to determine whether the traffic package of the Internet of Things card bound to the target traffic pool needs to be adjusted according to the traffic predicted by the traffic prediction unit and the traffic accumulated by the bonus traffic accumulation unit, and when it is determined that adjustment is needed, to the operator 10 The charging system sends the traffic plan adjustment indication information to instruct the charging system to adjust the traffic package for the at least one Internet of Things card bound to the target traffic pool. For example, the traffic plan adjustment indication information may be sent to the charging system of the operator 10 through the operator access integration.

Further, referring to FIG. 4, the Internet of Things application may further include an application gateway (APP Gateway) 414. The external browser may also query the traffic pool statistics analysis module 413 through the application portal 414 to query traffic pool statistics, such as a query. Each time interval in the fee period is the traffic provided by the target traffic pool consumed by the target traffic pool or the traffic provided by the traffic plan, or the traffic consumed by the target traffic pool or the traffic provided by the traffic plan.

Further, referring to FIG. 4, the Internet of Things application may further include a Product Cataloge (PC) module, a Rating module, a Billing & Payment module, a User Management (SUM) module, and management. Front desk (Portal) and so on. The ordering module is used to order the traffic package, and the rating module is used to wholesale traffic to the operator.

It should be noted that FIG. 4 is only an example in which the Internet of Things application includes the above module, and in practical applications, the Internet of Things application may further include more or less modules, or replace the module of FIG. 4, The application embodiment does not limit this.

It should be noted that, in the embodiment of the present application, only the traffic consumption record of the IoT card is obtained from the application module 411 by using the traffic pool statistics analysis module 413 as an example. In another embodiment, the traffic pool statistics analysis module 413 further The traffic consumption record of the IoT card can be obtained directly from the operator, for example, the traffic consumption record of the IoT card is obtained from the operator directly through the operator access integration, which is not limited by the embodiment of the present application.

FIG. 5 is a schematic structural diagram of a traffic packet adjustment apparatus according to an embodiment of the present application. The traffic package adjustment apparatus is used to implement a method for adjusting a traffic package for multiple user identifiers provided by an embodiment of the present application. Specifically, the traffic package adjustment device may be the traffic package adjustment device 40 in FIG. 1 or a device in the Internet of Things, such as a background server for an Internet of Things application. Referring to FIG. 5, the traffic plan adjustment device includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

The processor 501 can be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more program programs for controlling the embodiments of the present application. Execution of the integrated circuit.

Communication bus 502 can include a path for communicating information between the components described above.

The memory 503 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), or other information that can store information and instructions. Type of dynamic storage device, or Electro Scientific Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disc storage, optical disc Storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or capable of carrying or storing desired program code in the form of instructions or data structures and capable of being Any other medium accessed by the computer, but is not limited thereto. Memory 503 may be present independently and coupled to processor 501 via communication bus 502. The memory 503 can also be integrated with the processor 501.

Communication interface 504, using any type of transceiver, for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), and the like.

In a particular implementation, as an embodiment, processor 501 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG.

In a specific implementation, as an embodiment, the traffic plan adjustment device may include a plurality of processors, such as the processor 501 and the processor 505 shown in FIG. 2. Each of these processors can be a single-CPU processor or a multi-core processor. A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data, such as computer program instructions.

In a specific implementation, as an embodiment, the traffic plan adjusting device may further include an output device 506 and an input device 507. Output device 506 is in communication with processor 501 and can display information in a variety of ways. For example, the output device 506 can be a liquid crystal display (LCD), a light emitting diode (LED) display device, a cathode ray tube (CRT) display device, or a projector. Wait. Input device 507 is in communication with processor 501 and can receive user input in a variety of ways. For example, input device 507 can be a mouse, keyboard, touch screen device, or sensing device, and the like.

The above-mentioned traffic package adjustment device may be a general-purpose traffic package adjustment device or a dedicated traffic package adjustment device. In a specific implementation, the data package adjustment device may be a desktop computer, a portable computer, a network computer, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiment of the present application does not limit the type of the traffic package adjustment device.

The memory 503 is configured to store program code for executing the solution of the embodiment of the present application, and is controlled by the processor 501 for execution. The processor 501 is configured to execute the program code 508 stored in the memory 503. One or more software modules may be included in program code 508. The traffic plan adjustment device can implement the traffic plan adjustment for multiple user identifiers in the embodiment of the present application by using one or more software modules in the processor 501 and the program code 508 in the memory 503.

The method for adjusting the traffic package for multiple user identifiers provided in the embodiment of the present application is described in detail below.

FIG. 6 is a flowchart of a method for adjusting a traffic package for multiple user identifiers according to an embodiment of the present application, where the multiple user identifiers share the amount of traffic in the package provided by the operator. Referring to Figure 6, the method includes:

Step 601: Acquire a traffic package and a traffic consumption record corresponding to each user identifier of the multiple user identifiers before the current time point of the charging period.

The user identifier is used by the operator to identify the identity of the user, so that the operator can provide the mobile communication access service for the device according to the user identifier. In an actual application, the user identifier may be an identifier of a network card such as a SIM card, a UIM card, or an Internet of Things card, or may be an identifier of a user equipment or a user account.

The current traffic package of each user identifier refers to a traffic package subscribed in advance for the user identifier, and the traffic package of each user identifier may include the amount of traffic in the package included in the user identifier in each billing period. The unit price of the meter in the package and the unit price of the unit outside the package. The quantity of the line in the package refers to the total amount of traffic that the operator can provide for the user ID during the billing period based on the data package. In an actual application, the amount of traffic in the package may only include the amount of traffic that the user identifier purchases from the service provider through the data package, or may include the amount of traffic that the user identifier purchases from the service provider through the data package, and also includes The operator identifies the amount of additional traffic to the user based on the traffic plan.

In the embodiment of the present application, the multiple user identifiers can share the package traffic provided by the operator, and the package traffic provided by the shared operator refers to that the operator can provide each user identifier of the multiple user identifiers separately. The package traffic is aggregated together for the shared use of the multiple user identifiers, and each user identifier can use the package traffic of the multiple user identifiers according to actual needs, for example, the user identifier with a large traffic consumption can use the traffic within the package. The in-package traffic of the user ID with a large balance.

The billing period refers to an operator's billing period, and each billing period consists of multiple time intervals. For example, if the billing period is a natural month, each month consists of multiple natural days. The billing period refers to the billing period at which the current time point is located. For example, suppose the end of each month is the billing time of the operator. If the current time point is 1 am on November 20, the billing period at the current time point is the billing period in November.

It should be noted that the current time point is a time when the data package of the multiple user identifiers needs to be adjusted. In this embodiment, the data package of the multiple user identifiers may be adjusted in real time during the charging period. The adjustment time may also be set in advance. When the current time point reaches the preset adjustment time, step 301 is performed. The adjustment time may be any time in a billing period, and may be set according to actual needs. Moreover, in one billing period, one adjustment time may be set, or multiple adjustment times may be set. This example does not limit this. For example, the billing period is a natural month, the time interval is a natural day, and the billing period of the billing period is the end of the month. For example, the adjustment time can be set to the beginning of the month, the middle of the month, or the day before the end of the month, and of course, it can also be set to Other times, the embodiment of the present application does not limit this.

The traffic consumption record of each user identifier may record the traffic consumption of each user identifier. In actual applications, the traffic consumption record of each user identifier may be a bill file identified by each user. Specifically, the content of the CDR file of the target user identifier may include a target user identifier, a service traffic start time (Start Time), a service traffic end time (End Time), and a data traffic (Data Volume). The target user identifier is any one of the multiple user identifiers, and the target user identifier is the user identifier of the target network card. The target network card identifier may be the name of the target network card or the identification number of the target network card (Identity). , ID) and so on. In practical applications, the network card may also be referred to as an Integrated Circuit Card Identity (ICC), so the English abbreviation of the ID of the network card may be an ICCID. The data traffic refers to the total traffic consumed by the target user identifier in the time range of the service traffic start time and the service traffic usage end time. Further, the CDR file of the target user identifier may further include an accumulated consumption flow (Total Volume) of the operator identifier, the session identifier, and the target user identifier in the billing period. The identifier of the operator may be the name of the operator or the ID of the carrier (the carrier ID), and the session identifier may be a session name or a session ID.

Further, when the plurality of users are identified as identifiers of the plurality of Internet of Things cards in the Internet of Things, and the Internet of Things where the plurality of Internet of Things cards are located may be rented, and different Internet of Things enterprises are used as tenants. The mode of the CDR file of the target user identifier may further include a tenant identifier, where the tenant identifier is the identifier of the tenant to which the plurality of Internet of Things cards belong, and may be a tenant name or a tenant ID (Tenant). ID) and so on. Further, the content of the CDR file of the target user identifier may further include a service type. Specifically, the service type may be represented by an Access Point Name (APN) or an area identifier, and may also be represented by other methods. The embodiment does not limit this. The area identifier may be a zone name (Zone_Name) or an area ID (Zone_ID).

For example, taking the target user ID as the target IoT card identifier as an example, the target user identifier is within the bill file.

The format can be:

Tenant-id|carrier-id|SessionId|ICCID|StartTime|EndTime|DataVolume|APN|TotalVolume

Tenant-id is the tenant ID, carrier-id is the ID of the carrier, SessionId is the session ID, ICCID is the ID of the target IoT card, StartTime is the start time of the service traffic, EndTime is the end time of the service traffic, and DataVolume is Data traffic, APN is used to indicate the type of service, and TotalVolume is the cumulative consumption traffic.

For example, the identifiers of the plurality of user identifiers are taken as an example, and the billing period is a natural month, and each time interval is a natural day. The bill file obtained from the operator may be as shown in Table 1 below. Table 1 includes three CDR files, namely CDR file 1, CDR file 2, and CDR file 3. Among them, the CDR file 1 is the IoT card with the IoT card ID 12345678, and the traffic consumption in the time range from 19:14:15 on November 01, 2017 to 19:15:15 on November 01, 2017 Recorded, and the traffic consumed during this time range is 4196 Bytes, the cumulative consumption flow for the month is 4196 Bytes; the CDR file 2 is the IoT card with the IoT card ID 12345678 at 19:20:01 on November 01, 2017 - The flow consumption record in the time range of 19:25:15 on November 01, 2017, and the traffic consumed during this time range is 10240 Byte, the cumulative consumption flow of the month is 14436 Byte; the CDR file 3 is the Internet of Things card. The traffic consumption record of the IoT card with ID 12345679 in the time range from 8:22:15 on November 2, 2017 to 09:12:15 on November 2, 2017, and consumed within this time range The traffic is 2502 Bytes, and the cumulative consumption traffic for the month is 16938 Bytes.

Table 1

Field name	CDR file 1	CDR file 2	CDR file 3
Tenant-id	Vdiscovery	Vdiscovery	Vdiscovery
Carrier-id	100	100	100

SessionId	12345678	12345680	12356345
ICCID	12345678	12345678	12345679
StartTime	20171101191415	20171101192001	20171102082215
EndTime	20171101191515	20171101192515	20171102091215
DataVolume	4196	10240	2502
APN	Publicapn (public network)	Publicapn	Publicapn
TotalVolume	4196	14436	16938

It should be noted that, in the embodiment of the present application, only the content of the dialog file is described by using Table 1 as an example, but Table 1 does not constitute a limitation of the dialog file.

The traffic plan corresponding to the multiple user identifiers may be determined according to the data package change table of the multiple user identifiers, where the traffic plan change table of the multiple user identifiers is used to record the traffic of the multiple user identifiers. Package changes. Specifically, during the charging period, the traffic package change status of the multiple user identifiers may be recorded in real time, and the traffic package change table of the multiple user identifiers may be obtained, and the traffic that can be identified from the multiple user identifiers may be The package change table obtains the traffic package after the last change of the plurality of user identifiers, and determines the traffic package after the last change of the plurality of user identifiers as the traffic package corresponding to the plurality of user identifiers.

Further, when the method of the embodiment of the present application is applied to the Internet of Things, and the IoT card is bound to the traffic pool in the Internet of Things, the object traffic pool can be bound in real time during the use of the IoT card. The traffic package change status of all the IoT cards is recorded, and the traffic plan change table of the target traffic pool is obtained, and then the traffic plan change table of the target traffic pool can be obtained and bound to the target traffic pool. The data package after the last change of the plurality of Internet of Things cards activated in the period, and the data package after the last change of the plurality of Internet of Things cards is determined as the data package corresponding to the plurality of Internet of Things cards.

For example, Table 2 is a traffic plan change table of the target traffic pool provided by the embodiment of the present application. It is assumed that the traffic packages of each IoT card bound to the target traffic pool are the same, as shown in Table 2, the target traffic is known. The number of traffic in the package in the traffic package corresponding to each IoT card in the pool is 10M. Since the number of activations of the IoT card bound to the target traffic pool is 2 in the billing cycle, the target traffic pool is Total package traffic during the billing cycle = number of card activations * Intra-package traffic per card = 2*10M = 20M.

Table 2

Step 602: Predict the traffic consumption record corresponding to each user identifier in the multiple user identifiers before the current time point of the charging period, and predict the sum of the consumption flows of the multiple user identifiers in the charging period, and obtain a total forecast. Consumption flow.

Specifically, the traffic consumption record corresponding to each user identifier of the multiple user identifiers before the current time point of the charging period is predicted, and the sum of the consumption flows of the multiple user identifiers in the charging period is predicted, and the total prediction is obtained. Consumption traffic can include the following two implementations:

The first implementation manner is to collect statistics on the traffic consumption records of each user identifier in the multiple user identifiers before the current time point in the charging period, and obtain the multiple user identifiers before the current time point in the charging period. Actual consumption traffic; determining, according to the actual consumption traffic of the plurality of user identifiers before the current time point in the charging period, the predicted consumption traffic of the plurality of user identifiers after the current time point in the charging period; The user identifiers are added to the actual consumption traffic before the current time point in the billing period and the predicted consumption traffic after the current time point, and the predicted total consumption flows of the plurality of user identifiers in the billing period are obtained.

Specifically, the operation of predicting the predicted consumption flow after the current time point of the multiple user identifiers in the charging period may include: determining, according to the actual consumption traffic of the plurality of user identifiers before the current time point in the charging period. Calculating, from a starting time point of the charging period to a first total duration between the current time points, calculating a ratio between the actual consumption flow of the plurality of user identifiers before the current time point in the charging period and the first total time length Determining the ratio as the average consumption flow of the plurality of user identifiers within the first total duration, and then determining a second total duration from the current time point to the end time point of the billing period, and averaging the average The consumption flow is multiplied by the second total duration to obtain the predicted consumption flow of the plurality of user identifiers after the current time point in the billing period. Certainly, the embodiment of the present application may also use other manners to predict the predicted consumption traffic of the multiple user identifiers after the current time point in the charging period. The prediction manner used in this embodiment of the present application is not limited.

In the first implementation manner, the actual consumption flow before the current time point can be accurately obtained by using the current time point as the time interval, and the consumption flow after the current time point is predicted according to the actual consumption flow before the current time point, and then By adding the actual consumption flow before the current time point and the predicted consumption flow after the current time point, the predicted total consumption flow of the entire billing cycle can be accurately obtained with high accuracy.

Further, the method provided by the embodiment of the present application may also be applied to the Internet of Things, where the multiple user identifiers may also be identifiers of multiple Internet of Things cards sharing the service traffic given by the operator in the Internet of Things.

Further, in practical applications, the Internet of Things can also manage at least one (one or more) traffic pools, and can adjust the traffic packages of the Internet of Things card in units of traffic pools. When the adjustment time is reached, the identifiers of the plurality of the physical association cards activated in the charging period may be determined from the identifiers of all the Internet of Things cards that are bound to the target traffic pool, and then determined according to the method provided in the embodiment of the present application. The household consumption of the plurality of physical association cards indicates the predicted total consumption flow during the billing period. That is, the plurality of user identifiers may also be identifiers of a plurality of Internet of Things cards in the Internet of Things that are bound to the target traffic pool and activated during the billing cycle. The target traffic pool refers to any one of the at least one traffic pool managed by the Internet of Things.

Specifically, when the foregoing first implementation manner is used to predict the predicted total consumption traffic of the plurality of object-linked user identifiers in the billing period, the identifiers of all the Internet of Things cards bound to the target traffic pool are determined. The identification of the activated plurality of Internet of Things cards within the fee period includes: determining an identifier of the Internet of Things card that is bound to the target traffic pool and activated within a time range before the current time point within the billing period as the plurality of objects The identity of the network card.

The IoT card that is bound to the target traffic pool and is activated in the time range before the current time point in the charging period refers to the time range bound to the target traffic pool and within the time range before the current time point in the charging period. An IoT card in an activated state, the IoT card in an activated state includes an IoT card that is active and bound to a target traffic pool within a time range before a current time point in the billing cycle, or An IoT card that is overactive and bound to a target traffic pool for one or more periods of time or at a certain time in the time range prior to the current point in time during the billing cycle.

Specifically, in the process of using the IoT card in the charging period, the state change of the IoT card bound to the target traffic pool can be recorded in real time, and the state change table is obtained, and then determined from the state change table. A plurality of IoT cards that are bound by the target traffic pool and activated during the time range before the current time point in the billing cycle. The determining, by the state change table, the plurality of Internet of Things cards that are bound to the target traffic pool and activated in a time range before the current time point in the charging period includes: determining, from the state change table, that the original state is an active state The first IoT card bound to the target traffic pool in the billing period; the state change table determines that the destination state is the active state and the state change time is bound to the target traffic pool in the billing period. a second IoT card; determining a third IoT card bound to the target traffic pool that has been active from the start time of the billing cycle to the current time point; the first IoT card, the second IoT card And the third IoT card is determined to be a plurality of IoT cards that are bound to the target traffic pool and activated during a time range prior to the current time point within the billing cycle.

For example, Table 3 is a state change table of an Internet of Things card bound to a target traffic pool provided by an embodiment of the present application. It can be seen from Table 3 that the IoT card with the ICC ID of 12345678 has undergone a status change at "2017-11-1 10:04:03", and the changed status is active. The IoT card with the ICCID of 12345679 is in 2017. -11-2 10:05:04", a state change was made, and the changed state was activated. If the current time point is 2017-11-2 23:59:59, the number of activations of the IoT card bound to the target traffic pool in the billing cycle is 2, and the IoT card activated during the billing cycle is These two IoT cards.

table 3

The second implementation manner is: performing statistics on the traffic consumption records of each user identifier in the multiple user identifiers before the current time point in the charging period, and obtaining the actual number of the multiple user identifiers in at least one first time interval. The consumption flow, the at least one first time interval refers to at least one time interval from a first time interval of the charging period to the target time interval; and actual according to the plurality of user identifiers in the at least one first time interval Determining, by the consumption flow, a predicted consumption flow of the plurality of user identifiers in at least one second time interval, the at least one second time interval being at least one time interval after the target time interval within the billing period; And adding, by the plurality of user identifiers, the actual consumption traffic in the at least one first time interval and the predicted consumption traffic in the at least one second time interval, to obtain the multiple user identifiers in the charging period. Forecast total consumption traffic.

The target time interval refers to a segmentation time interval that needs to be used for statistical consumption flow and needs to predict consumption flow during the billing period, that is, for the target time interval in the billing period and the time interval before the target time interval, The actual consumption flows of the plurality of user identifiers are counted, and for the time interval after the target time interval in the billing period, the consumption flows of the plurality of user identifiers need to be predicted. In the embodiment of the present application, for convenience of description, each time interval between the first time interval in the charging period to the target time interval (including the target time interval) is referred to as a first time interval, and the target time interval is Each actual interval between the last time interval (excluding the target time interval) within the billing period is referred to as a second time interval.

Specifically, when the current time point is the end time of a time interval in the charging period, the target time interval is the current time interval in which the current time point is located, and the current time point is not a time interval in the charging period. At the end time, the target time interval is the most recent time interval before the current time point in the billing period.

When the current time point is the end time of a time interval in the billing period, considering that it is a complete time interval from the start time of the current time interval to the current time point, the actual consumption flow rate of the current time interval can be statistically obtained, so The current time interval may be used as the target time interval, and further as the first time interval; when the current time point is not the end time of a time interval in the charging period, that is, the current time point is included in any time interval within the charging period. When the time is other than the end time, considering that it is not a complete time interval from the start time of the current time interval to the current time point, the actual consumption flow of the current time interval cannot be completely counted, so the current time point can be The previous most recent time interval is taken as the target time interval, so that the current time interval is taken as the second time interval.

For example, the billing period is 11 months, the time interval is day, and the billing period of the billing period is the end of November. For example, if the current time point is the end time of November 20, that is, November 20, 23:59. 59 seconds, the target time interval is the time interval of the current time point, that is, November 20; if the current time point is not the end time of any day in November, for example, if the current time point is the start time of November 20 , that is, at 0:00:00 on November 20, the target time interval is the most recent time interval before the current time point in November, that is, November 19.

Specifically, the traffic consumption record of each user identifier in the multiple user identifiers before the current time point in the charging period is counted, and the actual consumption traffic of the multiple user identifiers in the at least one first time interval is obtained. Obtaining, for any of the first time intervals D in the at least one first time interval, a traffic consumption record of each of the plurality of user identifiers in the first time interval D; The traffic consumption records of the user identifiers in the first time interval D are counted, and the actual consumption traffic of the plurality of user identifiers in the first time interval D is obtained.

The traffic consumption record in the first time interval D is calculated for each of the plurality of user identifiers, and the actual consumption flow rate of the plurality of user identifiers in the first time interval D is obtained. The method includes: determining, according to the traffic consumption record of each of the plurality of user identifiers in the first time interval D, determining that each of the plurality of user identifiers is used in the first time interval D The traffic of the plurality of user identifiers used in the first time interval A is accumulated, and the actual consumption flow rate of the plurality of user identifiers in the first time interval A is obtained.

Further, in the embodiment of the present application, in the process of using, the actual consumption flow of the plurality of user identifiers may be counted in units of time intervals in time, and the traffic statistics in time interval units are obtained. The information table is configured to store the traffic statistics information table. When the current time point reaches the adjustment time that needs to adjust the traffic package of the multiple user identifiers, the at least one of the stored traffic statistics information tables is directly obtained. Actual consumption flow in the first time interval. Specifically, the actual consumption flow of the target flow pool may be counted in the time interval as a unit of time, or may be: in real time or every other time interval, the plurality of users are in time interval units. The actual consumption flow of the logo is counted.

The traffic statistics information table in the time interval includes the actual traffic statistics information in each time interval in the use process, and the actual traffic statistics information in each time interval in the use process includes but is not limited to: service type, current The time interval identifier, the billing period identifier, the usage flow rate of the current time interval, and the cumulative consumption flow rate of the current time interval. The usage traffic of the current time interval refers to the actual consumption traffic of the multiple user identifiers in the current time interval, that is, the total traffic actually consumed in the current time interval; the cumulative consumption traffic of the current time interval refers to the secondary charging. The total flow of accumulated consumption during the time range from the first time interval of the cycle to the current time interval.

Further, when the plurality of user identifiers are identifiers of the plurality of Internet of Things cards bound to the target process pool in the Internet of Things, the actual traffic statistics information of each time interval may further include the target traffic pool identifier and the current time interval. The number of card activations and the number of card activations for the billing cycle. The target traffic pool identifier may be a target traffic pool name (Volume Pool Name, VP_Name) or a target traffic pool ID (Volume Pool ID, VP_ID). The card activation number in the current time interval refers to the activation number of the IoT card bound to the target traffic pool in the current time interval; the card activation number in the charging period refers to the first time interval from the charging period to the current time interval. The cumulative number of activations of the IoT card bound to the target traffic pool over the time range.

For example, if the billing period is a natural month, each time interval is a natural day, the plurality of user identifiers are identifiers of the Internet of Things cards in the Internet of Things, and the Internet of Things uses the traffic pool as a unit for the traffic of the Internet of Things card. When the package is adjusted, in the process of using the IoT card, the actual consumption flow of the target traffic pool is counted in units of natural day as time progresses, and the traffic daily statistical information table of the target traffic pool in the process of use is obtained. The traffic daily statistics information table includes daily daily traffic consumption statistics during use. In a specific embodiment, the daily traffic consumption statistics may include: a target traffic pool identifier, a region identifier, a date (Calendar_Date), a month (Charge_cycle), a usage traffic of the current day (Used_Volume), a daily activation card number (Daily_Actice_Card_Number), and the current month. Card activation number (Month_Active_Card_Number). The usage traffic of the current day is used to indicate the traffic consumption value of the target traffic pool in the current day. The area identifier is used to indicate the type of service.

For example, if the billing period is a natural month and each time interval is a natural day, the daily traffic consumption statistical information table shown in Table 4 below can be obtained by counting the bill files of Table 1. Table 4 includes daily traffic consumption statistics 1 and daily traffic consumption statistics 2, and daily traffic consumption statistics 1 is daily traffic consumption statistics on November 1, 2017, and daily traffic consumption statistics 2 is November 2017. Daily traffic consumption statistics on the 02th. As can be seen from Table 4 below, the traffic consumption value of the target traffic pool on November 01, 2017 is 14436 Bytes, and the traffic consumption value on November 02, 2017 is 2502 Bytes.

Table 4

It should be noted that, in the embodiment of the present application, only the content of the daily traffic consumption statistical information table is described by using Table 4 as an example, but Table 3 does not constitute a limitation on the traffic consumption statistical information table. Moreover, the embodiment of the present invention is only described by using the Zone_Name as the service type. In the actual application, the service type may be represented by other letters or names.

Specifically, determining, according to the actual consumption traffic of the multiple user identifiers in the at least one first time interval, determining, by the plurality of user identifiers, the predicted consumption flows in the at least one second time interval, The actual consumption flow rate of the plurality of user identifiers in the at least one first time interval is predicted, and the predicted consumption flow rate of the plurality of user identifiers in the at least one second time interval is predicted by a preset moving average model method.

The preset moving average model method refers to a preset moving average model method. The sliding average model method refers to a method of predicting the data value of the next period or period by using a set of recent actual data values. The basic idea is to calculate the order-average average of a certain number of items according to the time series data. Value to reflect long-term trends. In the embodiment of the present application, the preset sliding average model method can accurately predict the traffic consumption trend of the target traffic pool in the future time interval, and can eliminate the effects of periodic fluctuations and random fluctuations, and the prediction accuracy is high.

Specifically, determining, according to the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval, by using a preset moving average model method, determining that the plurality of user identifiers are in the at least one second time interval. The predicted consumption traffic can include the following two implementations:

The first implementation manner is : for any of the at least one second time interval B, when the second time interval B is one of the first N time intervals in the charging period, and When the plurality of user identifiers do not have the actual traffic consumption record in the previous charging period of the charging period, the average value of the target consumption flows in all the time intervals before the second time interval B in the charging period is determined as The plurality of users identify predicted consumption flows in the second time interval B.

Where N is the number of time intervals that need to be smoothed according to the preset moving average model method in advance, and N is a positive integer. For any time interval C located before the second time interval B, when the plurality of user identifiers have actual consumption flows in the time interval C, the target consumption flow rate of the time interval C refers to the plurality of user identifications at the time The actual consumption flow in the interval C, when the plurality of user identifiers do not have actual consumption traffic in the time interval C, the target consumption flow rate of the time interval C refers to the predicted consumption of the plurality of user identifiers in the time interval C. flow.

When the second time interval B is one of the first N time intervals in the charging period, and the plurality of user identifiers do not have the actual traffic consumption record in the previous charging period of the charging period, Directly calculating an average value of target consumption flows of all time intervals before the second time interval B in the billing period, and determining the average value as the predicted consumption flow rate of the plurality of user identifiers in the second time interval B If the time interval with the flow consumption record before the second time interval B is less than N, the predicted moving average flow rate in the second time interval B can also be predicted by using the preset moving average model method.

For example, if N is 5, the billing period is month, the time interval is day, and the previous billing period of the billing period does not have an actual traffic consumption record. If the second time interval B is the second day of the billing period, The target consumption flow on the first day can be used as the predicted consumption flow for the next day. If the second time interval B is the third day of the billing cycle, the average of the target consumption flows of the first day and the second day may be used as the predicted consumption flow rate for the third day. If the second time interval B is the third day of the billing cycle, the average of the target consumption flows of the first day and the second day may be used as the predicted consumption flow rate for the third day. If the second time interval B is the fourth day of the billing cycle, the average of the target consumption flows of the first day, the second day, and the third day may be used as the predicted consumption flow rate for the fourth day. If the second time interval B is the fifth day of the billing cycle, the average of the target consumption flows of the first day, the second day, the third day, and the fourth day may be used as the predicted consumption flow rate for the fifth day.

The second implementation manner is : for any of the at least one second time interval B, when the second time interval B is one of the first N time intervals in the charging period, and The plurality of user identifiers are located when the actual traffic consumption record is recorded in the previous charging period of the charging period, or when the second time interval B is any time interval after the Nth time interval in the charging period, The average value of the target consumption flows of the N time intervals before the second time interval B is determined as the predicted consumption flow rate of the plurality of user identifiers in the second time interval B.

Wherein, N is a positive integer. For any time interval C before the second time interval B, when the plurality of user identifiers have actual consumption flows in the time interval C, the target consumption flow rate of the time interval C refers to The actual consumption flow rate of the plurality of user identifiers in the time interval C, when the plurality of user identifiers do not have actual consumption traffic in the time interval C, the target consumption flow rate of the time interval C means that the plurality of user identifiers are Predicted consumption traffic within time interval C.

Specifically, in the second implementation manner, the predicted consumption flow of the multiple user identifiers in the second time interval B may be determined by using the following formula:

among them,

Determining the predicted consumption flows in the second time interval B for the plurality of users, y ₁ , y ₂ , ..., y _N are respectively in the first 1, 2, ..., N time intervals of the second time interval B Target consumption flow, N is a positive integer.

That is, when the second time interval B is one of the first N time intervals in the charging period, and the plurality of user identifiers have actual traffic consumption records in the previous charging period of the charging period. When the time interval before the second time interval B in the charging period is less than N, the actual consumption flow rate of the last M time intervals can be obtained from the actual traffic consumption record of the previous charging period of the charging period. The target consumption flows of the M time intervals are supplemented by the M intervals to the time interval before the second time interval B in the charging period, and the target consumption values of the N time intervals are obtained. Where M is a positive integer, and the sum of M and the number of time intervals before the second time interval B in the billing period is equal to N. In addition, when the second time interval B is any time interval after the Nth time interval in the charging period, it indicates that the time interval before the second time interval B in the charging period is greater than or equal to N, and can be directly obtained at this time. The target amount consumption value of the N time intervals before the second time interval B in the billing period.

For example, if N is 5, the billing period is a natural month, the time interval is a natural day, and the previous billing period of the billing period has an actual traffic consumption record, if the second time interval B is the fifth day of the billing period. Then, the actual consumption flow of the last day of the previous billing period can be obtained from the actual traffic consumption record of the previous billing period of the billing cycle, as the target consumption flow of the last day of the previous billing period, and calculated before The average of the target consumption flow on the last day of a billing cycle and the target consumption flow of the first 4 days of the billing cycle, as the predicted consumption flow of the plurality of subscribers in the second time interval B. If the second time interval B is the sixth day of the charging period, the target consumption flow of the first 5 days of the charging period may be directly obtained, and the average value of the target consumption flow in the first 5 days of the charging period is calculated as the The predicted consumption flow rate of the plurality of user identifiers in the second time interval B is described.

In an embodiment, when the method in the embodiment of the present application is applied to the Internet of Things, and the Internet of Things adjusts the data package of the Internet of Things card in a flow pool, the target traffic pool may be bound in the charging period. In the process of using the IoT card, the actual consumption flow of the target flow pool is accumulated in real time in units of time intervals, and the predicted consumption flow in the future time interval is predicted. For example, FIG. 7 is a timing diagram of operation of a target traffic pool according to an embodiment of the present application. It is assumed that the charging period of the operator is a natural month, and the time interval in the charging period is a natural day, and the charging period is In the process of using the user ID, the CDR file of the IoT card bound to the target traffic pool can be obtained in real time, and the actual consumption traffic of the target traffic pool is accumulated according to the obtained CDR file, and the actual consumption traffic is accumulated according to the accumulated actual consumption traffic. The daily traffic consumption statistics of the user identifiers are predicted according to the daily traffic consumption statistics of the target traffic pool, and the predicted traffic consumption of the target traffic pool is predicted in the future, so that the daily traffic consumption prediction information of the target traffic pool is obtained. The traffic consumption statistical information and the daily traffic consumption prediction information are summarized to obtain the predicted total consumption traffic of the target traffic pool in the charging period. The predicted total consumption traffic of the target traffic pool in the charging period is the predicted total consumption traffic of the plurality of Internet of Things cards that are bound to the target traffic pool and activated during the charging period.

For example, based on Table 4 above, it can be known that the actual consumption flows of the target traffic pool in November 01, 2017 and November 02, 2017 are 14,436 Bytes and 2502 Bytes respectively. If the target traffic pool does not have a traffic consumption record in October 2017, , according to the actual consumption flow of the target traffic pool in November 01, 2017 and November 02, 2017, the forecasted consumption flow of the target traffic pool from November 3, 2017 to November 31, 2017 . Table 5 shows the traffic consumption records of the target traffic pool in November 2017, where the first two behavioral target traffic pools are actual consumption traffic within November 01, 2017 and November 02, 2017, respectively, followed by 29 behavioral traffic. The pool predicts consumption flows from November 3, 2017 to November 31, 2017, and the flow unit is Byte.

table 5

month	date	Traffic consumption of the target traffic pool
November 2017	1	14436
November 2017	2	2502
November 2017	3	8469
November 2017	4	8469
November 2017	5	8469
November 2017	6	8469
November 2017	7	7276
November 2017	8	8230
November 2017	9	8183
November 2017	10	8125
November 2017	11	8057
November 2017	12	7974
November 2017	13	8114
November 2017	14	8090
November 2017	15	8072
November 2017	16	8061
November 2017	17	8062

November 2017	18	8080
November 2017	19	8073
November 2017	20	8070
November 2017	twenty one	8069
November 2017	twenty two	8071
November 2017	twenty three	8073
November 2017	twenty four	8071
November 2017	25	8071
November 2017	26	8071
November 2017	27	8071
November 2017	28	8071
November 2017	29	8071
November 2017	30	8071
November 2017	31	8071

It should be noted that the embodiment of the present application only uses Table 5 as an example to describe the consumption traffic of the target traffic pool in one month, but Table 5 does not constitute a limitation on the target traffic pool consumption traffic.

Further, if the method provided by the embodiment of the present application is applied to the Internet of Things, and the Internet of Things adjusts the data package of the Internet of Things card by using the traffic pool, when the traffic plan of the target traffic pool needs to be adjusted, The plurality of IoT cards activated in the billing period may be determined from all the IoT cards that are bound to the target traffic pool, and then the identifiers of the plurality of IoT cards are predicted according to the method provided in the embodiment of the present application. Total consumption flow during the fee period. That is, the plurality of user identifiers may also be identifiers of a plurality of Internet of Things cards in the Internet of Things that are bound to the target traffic pool and activated during the billing cycle.

Specifically, when the foregoing second implementation manner is used to determine the predicted total consumption traffic of the identifiers of the plurality of Internet of Things cards in the billing period, the identifiers of all the Internet of Things cards bound to the target traffic pool are determined. The identification of the activated plurality of IoT cards during the billing period includes: determining an identifier of the IoT card that is bound to the target traffic pool and activated within a time range in which the at least one first time interval is located The identification of multiple IoT cards.

The IoT card that is bound to the target traffic pool and activated in the time range in which the at least one first time interval is located is bound to the target traffic pool and is located in the at least one first time interval. An IoT card that is in an active state within a time range, the IoT card in an overactive state includes being active and bound to the target traffic pool for a time range in which the at least one first time interval is located An IoT card, or an IoT card that is active and bound to the target traffic pool for one or more times or at a certain time in the time range in which the at least one first time interval is located.

Specifically, during the use of the Internet of Things card in the billing cycle, the state change of the IoT card of the standard traffic pool can be recorded in real time, and a state change table is obtained, and then the target change table is determined and targeted. The total number of IoT cards that are bound by the traffic pool and activated during the time range in which the at least one first time interval is located. Determining, from the state change table, an IoT card that is bound to the target traffic pool and activated in a time range in which the at least one first time interval is located includes: determining, from the state change table, that the original state is an active state The fourth IoT card bound to the target traffic pool in the billing period; the state change table determines that the destination state is the active state and the state change time is bound to the target traffic pool in the billing period. The fifth Internet of Things card; determining the sixth Internet of Things card bound to the target traffic pool that has been active from the start time of the billing period to the current time point; the fourth Internet of Things card, the fifth Internet of Things card And the sixth Internet of Things card is determined to be an IoT card that is bound to the target traffic pool and activated within a time range in which the at least one first time interval is located.

Further, when the data package of the plurality of user identifiers includes a traffic package of different service types, and the traffic package of the target service type of the multiple user identifiers needs to be adjusted, the current time in the charging cycle may also be used. The traffic consumption record of each user identifier in the plurality of user identifiers is predicted, and the total consumption traffic of the target service type of the plurality of user identifiers in the billing period is predicted, and the predicted total consumption traffic of the target service type is obtained. And according to the predicted total consumption traffic of the target service type in the charging period and the data package of the target service type corresponding to each user identifier, the traffic plan of the target service type identified by the multiple users Make adjustments. The target service type may be any one of multiple service types supported by the multiple user identifiers.

In an embodiment, the service types supported by the multiple user identifiers may also be classified according to specific value-added service types. For example, the service types supported by the Internet of Things may include a music type, a video type, and a short message type. Of course, the service type supported by the Internet of Things can also be classified according to other types, which is not limited in this embodiment of the present application.

In another embodiment, when the plurality of users are identified as identifiers of the plurality of Internet of Things cards in the Internet of Things, the service types supported by the plurality of user identifiers may further include a targeted service type and a public network service type. The directional service type refers to the service accessing the Internet of Things, and the public network service refers to the service outside the Internet of Things. Moreover, in practical applications, the service of the targeted service type is usually paid by the Internet of Things service provider, and is generally free for the Internet of Things users, while the business of the public network type needs to be paid by the Internet of Things users.

Specifically, determining a predicted total consumption flow of the target service type of the multiple user identifiers in the charging period according to the traffic consumption record of each of the plurality of user identifiers before the current time point in the charging period The traffic statistics process and the traffic prediction process for all service types of the multiple user identifiers in the foregoing implementation process are switched to the traffic statistics process and the traffic prediction process for the target service type of the multiple user identifiers. The embodiments of the present application are not described herein again.

In a specific embodiment, when the plurality of users are identified as identifiers of the plurality of Internet of Things cards that are bound to the target traffic pool and activated during the charging period in the Internet of Things, and determined by using the second implementation manner. When the identifiers of the plurality of Internet of Things cards are used to predict the total consumption traffic during the billing period, referring to FIG. 4, for any of the at least one first time interval, the first time interval D may be used by the Internet of Things application. The application module 411 acquires the bill file of the plurality of Internet of Things cards bound to the target traffic pool in the first time interval D, and binds the plurality of Internet of Things bound to the target traffic pool. The CDR file in the first time interval D is sent to the traffic pool statistics analysis module 413 by the kafka message, and the traffic pool statistics analysis module 413 is configured according to the CDR file in the first time interval D according to the plurality of Internet of Things cards. The actual consumption flow rate of the identifier of the plurality of Internet of Things cards in the first time interval D is counted, and the actual consumption flow rate of the target traffic pool in the first time interval D is obtained. Then, determining, according to the actual consumption flow rate of the identifiers of the plurality of Internet of Things cards in the at least one first time interval, the predicted consumption flows of the identifiers of the plurality of Internet of Things cards in at least one second time interval, and Adding the actual consumption flow rate of the identifiers of the plurality of Internet of Things cards in the at least one first time interval and the predicted consumption flow rate in the at least one second time interval to obtain the plurality of Internet of Things The NIC identifies the total consumption traffic during the billing period.

Step 603: Send, according to the predicted total consumption traffic and the traffic plan corresponding to each user identifier of the multiple user identifiers, the traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system is the At least one of the plurality of user identifiers adjusts the traffic plan, so that the settlement fee of the plurality of user identifiers that are settled with the operator according to the adjusted traffic plan in the billing period is less than the traffic according to the adjustment The settlement fee for settlement of the package with the operator.

The traffic package of each user identifier includes the amount of traffic in the package within the charging period, the unit price of the package outside the package, or the price of the package. The traffic plan adjustment indication information includes the at least one user identifier and the new traffic package of the at least one user identifier, and the at least one user identifier and the new traffic package of the at least one user identifier are based on the predicted total consumption flow and The traffic plan corresponding to each user identifier of the plurality of user identifiers is determined, and the traffic package included in the traffic package corresponding to the at least one user identifier is different from the new traffic package included in the at least one user identifier. The amount of traffic within the package.

The traffic package adjustment indication information may be sent to the operator's charging system according to a communication protocol negotiated with the operator through an interface with the operator. For example, the traffic plan adjustment indication information can be sent to the operator according to the Simple Object Access Protocol (SOAP) interface of the Hyper Text Transfer Protocol (HTTP) according to the SOAP protocol of HTTP. The adjustment indication information can be shaped like:

Specifically, the sending the data package adjustment indication information to the charging system of the operator according to the predicted total consumption traffic and the traffic package corresponding to each user identifier of the multiple user identifiers includes:

Step 6031: Accumulate the amount of the in-package traffic in the data package corresponding to each user identifier of the multiple user identifiers, and obtain the total package traffic.

Specifically, the amount of the in-package traffic in the data package corresponding to each of the plurality of user identifiers is accumulated, and the total package traffic is obtained by: determining, according to the traffic package of each user identifier of the multiple user identifiers, The amount of the in-package traffic in the traffic plan corresponding to each user identifier of the plurality of user identifiers, and the amount of the in-package traffic in the traffic package corresponding to each of the plurality of user identifiers is added to obtain the total package. flow.

Further, when the traffic packages corresponding to the multiple user identifiers are the same, the number of traffic in the package in the traffic package corresponding to one of the multiple user identifiers may be determined, and then the traffic package corresponding to the user identifier is determined. The amount of traffic in the package in the package is multiplied by the number of the plurality of user identifiers to obtain the total package traffic.

Further, when determining, by using the first implementation in the foregoing step 301, the predicted total consumption traffic of the multiple user identifiers in the charging period, in the charging period, the current time interval may also be configured in real time. The package traffic for traffic and billing cycles is accumulated. The package traffic of the current time interval is the sum of the average package flows of the multiple user identifiers in each time interval. For example, if each user identifies monthly traffic within the package is 600M traffic, and there are 30 days in the current month, the average daily package traffic per user identity is 600M/30=20M, if the number of the multiple user identifiers is 10, the plurality of user identifiers have a daily package flow rate of 20M*10=200M. The packet flow of the charging period refers to the sum of the package flows in the time range from the first time interval of the charging period to the current time interval. For example, if the current day is the middle of the month, each user ID has a monthly in-package flow of 200M, then the package flow value of each user identifier from the first day to the current time is 200M/2=100M, if the If the number of multiple user identifiers is 10, the package traffic of the billing cycle is 100M*10=1000M. By accumulating the package traffic of the current time interval and the package traffic of the billing cycle, it is possible to timely reflect the change of the package traffic of the plurality of user identifiers over time.

Further, when the method of the embodiment of the present application is applied to the Internet of Things, and the IoT card in the Internet of Things is bound to the traffic pool, the package traffic of the target traffic pool in the current time interval and the charging period can be accumulated in real time. The package traffic, which reflects the change in the package traffic of the target traffic pool over time. The packet traffic of the target traffic pool in the current time interval may be determined according to the activation quantity of the IoT card bound to the target traffic pool in the current time interval, and the packet traffic of the target traffic pool in the charging cycle may be based on the target traffic. The number of activations of the pool-bound IoT card during the billing cycle is determined.

In an embodiment, referring to FIG. 7, during the use of the IoT card in the billing cycle, the traffic consumed by the target traffic pool is accumulated and predicted, and the target traffic pool is also bound in real time. The status change data of the IoT card is counted according to the status change data, and the card activation number of the IoT card bound to the target traffic pool in the billing period is counted, and the activation quantity is obtained, and the package in the billing period is determined according to the activation quantity. The traffic is accumulated.

Further, when the plurality of user identifiers include the traffic plan of different service types, and the traffic plan of the target service type of the multiple user identifiers needs to be adjusted, the target corresponding to the multiple user identifiers may also be used. a service type traffic package, determining a total package traffic of the target service type of the plurality of user identifiers in a billing period, and then predicting a total consumption traffic amount of the target service type in the billing period according to the plurality of user identifiers The total package traffic is adjusted for the traffic plan of the target service type of the plurality of user identifiers.

Step 6032: Determine a first difference between the predicted total consumption flow and the total package flow.

Step 6033: Send the data package adjustment indication information to the charging system of the operator according to the first difference.

By determining the first difference between the predicted total consumption flow and the total package flow, the predicted total consumption flow can be compared with the total package flow, and then the flow plan of the charging cycle is automatically adjusted according to the comparison result.

For example, referring to Figure 7, taking the target traffic pool managed by the Internet of Things as an example, during the use of the IoT card in the billing cycle, the total consumption traffic of the target traffic pool can be accumulated and predicted, and the target traffic pool is obtained. The total estimated consumption flow in the billing cycle is accumulated, and the total package traffic of the target traffic pool in the billing period is obtained. When the current time point is adjusted, the traffic plan of the target traffic pool needs to be adjusted. At the time, the target total traffic pool can be compared with the total package traffic in the billing cycle, and then the traffic plan of the target traffic pool is adjusted according to the comparison result.

Further, before the sending the data package adjustment indication information to the charging system of the operator, the first difference is greater than or equal to the preset threshold, and the first difference is greater than or equal to the preset. At the threshold, the adjustment information is further determined according to the determination, and the traffic package adjustment indication information is sent to the charging system of the operator according to the adjustment information. The adjustment information may include at least one user identifier to be adjusted among the multiple user identifiers and a new traffic package of the at least one user identifier. The preset threshold may be preset and may be set according to actual needs. For example, the preset threshold may be set to 0 KB, 100 KB, or 500 KB, and the like.

In other words, when the first difference between the predicted total consumption traffic and the total package traffic is greater than or equal to the preset threshold, the traffic plan of the charging cycle is adjusted, when the preset threshold is less than , indicating that the difference between the two is small, the settlement tariff under the current traffic package is not much different from the total traffic package. In this case, the traffic schedule of the billing cycle may not be adjusted.

Specifically, sending the data package adjustment indication information to the charging system of the operator according to the first difference may include the following three implementation manners:

The first implementation manner is: if the traffic packets corresponding to the multiple user identifiers are different, the prediction may be determined when the first difference is greater than or equal to a preset threshold and the at least one user identifier is the multiple user identifiers. a first ratio between the total consumption traffic and the total package traffic, and then determining, according to the first ratio, a new traffic package of the at least one user identity, and according to the at least one user identity and the at least one user identity The new traffic package sends the traffic plan adjustment indication information to the charging system of the operator to instruct the charging system to adjust the traffic plan of the at least one user identifier to a corresponding new data package.

The at least one user identifier indicates that the plurality of user identifiers can uniformly adjust the traffic packages of the plurality of user identifiers, and, according to the ratio between the predicted total consumption traffic and the total package traffic, Performing a proportional adjustment on the traffic package of each of the plurality of user identifiers, thereby implementing adaptive adjustment of the traffic package of each user identifier according to the overall traffic consumption of the multiple user identifiers. This adjustment method allows for precise adjustment of the traffic plan for each user ID.

Further, before determining the new traffic package of the at least one user identifier, the first ratio may be rounded off, and the number of digits after the decimal point is a preset number of digits, and then according to the first ratio. After processing the first ratio, determining a new traffic package of the at least one user identifier. The preset number of bits can be preset. For example, the preset number of bits can be 0, 1, or 2.

Specifically, the determining, according to the first ratio, the operation of the new traffic plan of the at least one user identifier may include: determining, in any one of the at least one user identifier, the traffic plan corresponding to the user identifier A The product of the amount of traffic in the package and the first ratio, according to the product, from the plurality of traffic packages provided by the operator, the traffic package having the smallest difference between the number of traffic in the package and the product is determined as the user identifier A. a traffic package, or determining, from the plurality of traffic packages, a traffic package having a traffic quantity greater than or equal to the product and having a smallest difference from the product as a traffic package of the user identifier A, or from the In the plurality of traffic packages, the traffic plan with the minimum settlement tariff between the operator and the operator in the case where the total consumption flow of the user identifier A in the charging period is equal to the product is determined as the traffic package of the user identifier A.

For example, as shown in the following Table 6, it is assumed that there are three user identifiers, and the current traffic package of the three user identifiers is determined: the traffic package of the user identifier 1 is 20 yuan per month, and the traffic package of the user identity 2 is 20 yuan. 500M per month, the traffic package of User ID 3 is 100 yuan per month, and the total package traffic of these 3 user IDs in the billing cycle is 1.7G. In addition, it is assumed that the current time point prediction result is: the predicted total consumption traffic of the user identifier 1 in the billing period is 150M, the predicted total consumption traffic of the user identifier 2 in the billing period is 600M, and the user identifier 3 is within the billing period. The predicted total consumption flow is 800M, and the total consumption flow of the three user IDs in the billing cycle is 1.55G. It can be seen that the first ratio of the total consumption traffic of the three user identifiers in the billing cycle to the total package traffic is 1.55G/1.7G=0.91, and accordingly, the package traffic of the user identifier 1 needs to be adjusted to 200M*0.91. =182M, the package traffic of user identification 2 is adjusted to 495M*0.91=495M, and the package traffic of user identification 3 is adjusted to 1G*0.91=910M.

It is assumed that the plurality of data packages provided by the operator for the multiple user identifiers include the traffic packages with the number of traffic in the package equal to 182M, 495M, and 910M, respectively, and the traffic package with the number of traffic within the package equal to 182M can be determined as the user identifier. The new traffic package of 1 will determine the traffic package with the traffic volume equal to 495M in the package as the new traffic package of user identification 2, and determine the traffic package with the traffic quantity equal to 910M in the package as the new traffic package of user identification 3.

Table 6

Current data package

forecast result

New traffic package

User ID 1	200M	150M	182M
User ID 2	500M	600M	495M
User ID 3	1G	800M	910M
Total value	1.7G	1.55G

In addition, for the user identifier 3, when the plurality of traffic packages does not include the traffic package with the number of traffic in the package equal to 910M, the traffic package with the smallest difference between the traffic volume in the package and the 910M, for example, may be used. The traffic plan with the number of traffic in the package is equal to 900M, and it is determined as the new traffic package of User ID 3. Alternatively, a traffic package with a traffic volume greater than 910M and a minimum difference between the 910M and the 910M, such as a traffic package with a traffic volume equal to 950M, may be determined as a new traffic package of the user identity 3. Alternatively, a traffic plan that can minimize the total settlement traffic of the user identifier 3 in the billing period is equal to 910M, and the traffic bill with the lowest settlement tariff of the operator is determined as the new traffic package of the user identifier 3.

The second implementation manner is: when the traffic packets corresponding to the multiple user identifiers are the same, the first difference is greater than or equal to a preset threshold, and the at least one user identifier is determined by the multiple user identifiers. Determining a second ratio between the total consumption traffic and the quantity of the at least one user identifier, and then determining, according to the second ratio, a new traffic package of the at least one user identity, according to the at least one user identity and the The at least one user-identified new data package sends the data package adjustment indication information to the charging system of the operator to instruct the charging system to adjust the traffic plan of the at least one user identifier to a corresponding new data package.

The at least one user identifier indicates that the plurality of user identifiers can be uniformly adjusted for the traffic metrics of the multiple user identifiers, and the foregoing ones of the plurality of user identities can be pre-charged according to the user identifiers. The average consumption flow in the period is adjusted, and the traffic package of the multiple user identifiers is adjusted, so that the average traffic consumption of each user identifier in the multiple user identifiers may be adjusted, and the traffic package of each user identifier is uniformly adjusted. This adjustment method can reduce the amount of calculation and improve the adjustment efficiency.

Further, according to the second ratio, before determining the new traffic package of the at least one user identifier, the second ratio may be rounded off, and the number of digits after the decimal point is a preset number of digits, and then After processing the second ratio, determining a new traffic package of the at least one user identifier. The preset number of bits can be preset. For example, the preset number of bits can be 0, 1, or 2.

Specifically, the determining, according to the second ratio, the operation of the new traffic package of the at least one user identifier may include: for any one of the at least one user identifier, according to the second ratio, from the operator In the plurality of data packages provided, determining a traffic package having the smallest difference between the number of traffic in the package and the second ratio as a new traffic package of the user identifier A, or determining from the plurality of traffic packages a traffic package having a traffic quantity greater than or equal to the second ratio and having a smallest difference from the second ratio as a traffic package of the user identifier A, or determining, from the plurality of traffic packages, the user The traffic plan with the smallest settlement tariff with the operator in the case where the total consumption flow in the charging period is equal to the second ratio is used as the new traffic package of the user identifier A.

For example, suppose the target traffic pool has a total package traffic of 20M in the current month, the predicted total consumption traffic is 244KB, and the number of activations of the IoT card bound to the target traffic pool in the current month is 2, then the second ratio is 244KB/2= 122KB. When the traffic plan provided by the operator for the target traffic pool includes the traffic plan with the number of traffic in the package equal to 122KB, the traffic plan with the number of traffic within the package equal to 122KB can be determined as the identifier of the two IoT cards. The new traffic package, and according to the identification of the two IoT cards and the new traffic package of the identification of the two IoT cards, send the traffic package adjustment indication information to the carrier's charging system to indicate that the charging system will The traffic package of the at least one user identifier is adjusted to a corresponding new traffic package. For example, the adjusted traffic plan change table can be as follows:

Table 7

Field name	Traffic plan change record
RATE_PLAN_ID	112
RATE_PLAN_NAME	1234
RATE_PLAN_TYPE	1 (monthly payment)
TOTAL_VOLUME	122KB

a third implementation manner: when the first difference is greater than or equal to a preset threshold, determining a third ratio between the first difference and the quantity of the at least one user identifier, and determining the at least the third ratio according to the third ratio a new traffic package of the user identifier, sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system is to be The traffic package of the at least one user identifier is adjusted to the corresponding new traffic package.

In a third implementation manner, the at least one user identifier may be the multiple user identifiers, or may be part of the multiple user identifiers, when the at least one user identifier is the multiple A part of the user identifiers in the user identifier can be adjusted only for the traffic packets of some user identifiers, and the traffic packages of all the user identifiers need not be adjusted, thereby simplifying the adjustment operation and improving the adjustment efficiency. The at least one user identifier may be configured by the user, may be set by the system by default, or may be selected by the system according to a preset policy.

The third ratio is the in-package traffic that needs to be adjusted for each user identifier in the at least one user identifier, that is, in the embodiment of the present invention, the at least one user may be configured according to the first difference. The traffic within the identified package is adjusted on average, so that the traffic within the package adjusted by each user ID is the same.

Specifically, according to the third ratio, the implementation of determining the new traffic package of the at least one user identifier may include the following manners 1) and 2):

Mode 1): When the predicted total consumption traffic is less than the total package traffic, for any user identifier A in the at least one user identifier, the number of in-package traffic in the traffic package corresponding to the user identifier A may be determined. a second difference between the three ratios, and then determining, according to the second difference, the traffic with the smallest difference between the amount of traffic in the package and the second difference from the plurality of data packages provided by the operator The package is used as a new traffic package of the user identifier A, or from the plurality of traffic packages, determining a traffic package in which the amount of traffic in the package is greater than or equal to the second difference and the difference between the second difference is the smallest As a new traffic package of the user identifier A, or from the plurality of traffic packages, determining that the total consumption flow of the user identifier A in the billing period is equal to the second difference, and the carrier The minimum traffic plan for settlement tariffs is used as the new traffic package for User ID A.

That is, when the predicted total consumption traffic is less than the total package traffic, the in-package traffic of each user identity may be decreased according to the third ratio, so that the adjusted package traffic of the multiple user identifiers is included. The total package traffic is approaching the predicted total consumption traffic, that is, the adjusted package traffic of the plurality of user identifiers can meet the actual traffic consumption demand of the multiple user identifiers, thereby enabling the multiple user identifiers and operations. The settlement fee between merchants is reduced.

Mode 2): When the predicted total consumption traffic is greater than the total package traffic, for any user identifier A in the at least one user identifier, the number of traffic in the package in the traffic package corresponding to the user identifier A may be determined. The sum of the three ratios, and then according to the sum value, from the plurality of data packages provided by the operator, determine the traffic package with the smallest difference between the number of flows in the package and the sum value as the user identifier A. a new traffic package, or a traffic plan that determines that the amount of traffic in the package is greater than or equal to the sum and the difference from the sum is the new traffic plan of the user identifier A, or from the plurality of traffic packages. In the plurality of traffic packages, a traffic plan with the lowest settlement tariff between the operator and the operator in the case where the total consumption traffic of the user identifier A in the charging period is equal to the sum value is determined as the new user identifier A. Data Package.

That is, when the predicted total consumption traffic is greater than the total package traffic, the in-package traffic of each user identity may be increased according to the third ratio, so that the adjusted package traffic included in the multiple user identifiers is included. The total package traffic approaches the predicted total consumption traffic, that is, the adjusted package traffic of the plurality of user identifiers can meet the actual traffic consumption demand of the multiple user identifiers, thereby causing the multiple user identifiers and operators The settlement fee between the reduction is reduced.

Further, when the traffic package of the plurality of user identifiers includes a traffic package of a different service type, and the traffic package of the target service type of the multiple user identifiers needs to be adjusted, the multiple user identifiers may also be determined according to the multiple user identifiers. Determining a total traffic flow of the target service type of the at least one user identity and a total package flow of the target service type within the billing period, and determining the target according to the at least one user identifier and the at least one user identifier a new traffic plan of the service type, the network package adjustment indication information is sent to the charging system of the operator, where the data package adjustment indication information includes the at least one user identifier and the new traffic package of the target service type of the at least one user identifier And indicating that the charging system adjusts the traffic plan of the target service type of the at least one user identifier to a corresponding new traffic package. The traffic package of the target service type of each user identifier includes the amount of the in-package traffic of the target service type of the user identifier in each billing period, the package price, and the unit price of the outbound package. In the specific implementation process, the traffic package adjustment process for all the service types identified by the multiple users in the foregoing implementation process may be switched to the traffic package adjustment process for the target service type of the multiple user identifiers. The embodiments of the present application are not described herein again.

The traffic of the target service type of the plurality of user identifiers is adjusted and predicted according to the statistics and the prediction result, and the traffic package of the target service type of the at least one user identifier of the multiple user identifiers is adjusted, thereby realizing The fine adjustment of the traffic packages of the plurality of user identifiers can meet the needs of different users and improve the user experience.

In the embodiment of the present application, the traffic package and the traffic consumption record corresponding to each user identifier in the multiple user identifiers before the current time point of the charging period may be obtained at any time in the charging period, and then according to the current time point. a traffic consumption record of each user identifier in the user identifier, predicting a sum of consumption flows of the plurality of user identifiers in a billing period, and obtaining a predicted total consumption traffic, according to the predicted total consumption traffic and each user identifier corresponding to the The traffic plan sends the traffic plan adjustment indication information to the charging system of the operator, where the data package adjustment indication information includes at least one user identifier and a corresponding new traffic package of the multiple user identifiers, to indicate that the charging system is The at least one user identifier adjusts the traffic plan to reduce the settlement fee of the plurality of user identifiers and the operator. That is, the total consumption traffic of the plurality of user identifiers in the billing period can be accurately predicted at any time within the billing period, and the traffic plan of the plurality of user identifiers is automatically performed according to the predicted total consumption traffic. The adjustment makes the settlement fee of the current billing cycle minimize. Compared with the artificial adjustment method in the related art, the adjustment method is more timely and more accurate, and the user can further save the settlement fee, and the flexibility is high.

FIG. 8 is a schematic structural diagram of an apparatus for adjusting a traffic package for multiple user identifiers according to an embodiment of the present disclosure. The multiple user identifiers share the number of flows in the package provided by the operator. Referring to FIG. 8, the device may include:

The obtaining module 801 is configured to perform step 601 in the foregoing embodiment of FIG. 6;

a prediction module 802, configured to perform step 601 in the foregoing embodiment of FIG. 6;

The sending module 803 is configured to perform step 601 in the foregoing embodiment of FIG. 6.

Optionally, the sending module 803 includes:

The accumulating unit is configured to accumulate the amount of the in-package traffic in the data package corresponding to each user identifier of the multiple user identifiers, to obtain the total package traffic;

a first determining unit, configured to determine a first difference between the predicted total consumption traffic and the total package traffic;

And a sending unit, configured to send the data package adjustment indication information to the charging system of the operator according to the first difference.

Optionally, the traffic packages corresponding to the multiple user identifiers are different.

The sending unit is specifically configured to:

Determining, when the first difference is greater than or equal to a preset threshold, and the at least one user identifier is the plurality of user identifiers, determining a first ratio between the predicted total consumption traffic and the total package traffic;

Determining, by any one of the at least one user identifiers A, a product of the number of in-package traffic in the traffic plan corresponding to the user identifier A and the first ratio;

According to the product, a traffic plan with the smallest difference between the number of traffic in the package and the product is determined as the traffic package of the user identifier A, or from the plurality of traffic packages provided by the operator. In the plurality of traffic packages, determining, by the traffic plan that the number of traffic in the package is greater than or equal to the product, and the difference between the products is the traffic package of the user identifier A, or from the multiple traffic In the package, determining, as the user identifier A, a traffic plan with the minimum settlement tariff between the user identifier A and the operator in the case where the total consumption flow in the billing period is equal to the product Data Package;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

Optionally, the traffic packages corresponding to the multiple user identifiers are the same;

The sending unit is specifically configured to:

Determining a second between the predicted total consumption traffic and the quantity of the at least one user identifier when the first difference is greater than or equal to a preset threshold and the at least one user identifier is the plurality of user identifiers ratio;

Determining, between the plurality of traffic packages provided by the operator, between the number of traffic in the package and the second ratio, according to the second ratio, The traffic plan with the smallest difference is used as the new traffic package of the user identifier A, or from the plurality of traffic packages, determining that the amount of traffic in the package is greater than or equal to the second ratio and between the second ratio The traffic plan with the smallest difference is used as the traffic package of the user identifier A, or from the plurality of traffic packages, determining that the total consumption traffic of the user identifier A in the billing period is equal to the first In the case of the second ratio, the traffic plan with the lowest settlement tariff of the operator is used as the new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

Optionally, the sending unit is specifically configured to:

Determining, when the first difference is greater than or equal to a preset threshold, a third ratio between the first difference and the number of the at least one user identifier;

When the predicted total consumption traffic is less than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic plan corresponding to the user identifier A, and the number a second difference between the three ratios;

Determining, according to the second difference, a traffic plan with the smallest difference between the number of flows in the package and the second difference from the plurality of data packages provided by the operator as the user identifier A a new traffic package, or a traffic plan from the plurality of traffic packages that determines that the amount of traffic in the package is greater than or equal to the second difference and the difference between the second difference is the smallest Identifying a new traffic package of A, or determining, from the plurality of traffic packages, that the total consumption flow of the user identifier A in the charging period is equal to the second difference, and the operation The traffic plan with the lowest settlement tariff between the merchants is used as the new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

Optionally, the sending unit is specifically configured to:

When the predicted total consumption traffic is greater than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic package corresponding to the user identifier A, and the number The sum between the three ratios;

Determining, according to the sum of the plurality of data packages provided by the operator, a traffic package having the smallest difference between the number of traffic in the package and the sum value as the new traffic package of the user identifier A, Or determining, from the plurality of data packages, a traffic package whose amount of traffic in the package is greater than or equal to the sum value and having a smallest difference from the sum, as a new traffic package of the user identifier A, or And determining, in the plurality of traffic packages, a traffic plan having a minimum settlement tariff with the operator when the total consumption flow of the user identifier A in the charging period is equal to the sum value The new traffic package of the user identifier A;

And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.

Optionally, the prediction module 802 includes:

a statistical unit, configured to perform statistics on the traffic consumption record, to obtain actual consumption traffic of the multiple user identifiers in at least one first time interval, where the at least one first time interval refers to the charging period The first time interval to at least one time interval of the target time interval;

Wherein, when the current time point is the end time of a time interval in the charging period, the target time interval is a time interval in which the current time point is located, and when the current time point is not a time interval in the charging period The end time interval is the latest time interval before the current time point in the billing period;

a second determining unit, configured to determine, according to actual consumption traffic of the multiple user identifiers in the at least one first time interval, a predicted consumption flow rate of the multiple user identifiers in at least one second time interval, where The at least one second time interval refers to at least one time interval after the target time interval in the charging period;

a processing unit, configured to add, between the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval and the predicted consumption flow rate in the at least one second time interval, to obtain the total prediction Consumption flow.

Optionally, the second determining unit is specifically configured to:

Determining, according to the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval, a predicted consumption of the plurality of user identifiers in the at least one second time interval by a preset moving average model method flow.

Optionally, the second determining unit is specifically configured to:

For any of the at least one second time interval B, when the second time interval B is one of the first N time intervals within the charging period, and the plurality of time intervals When the user ID does not have a data traffic consumption record in the previous billing period of the billing period, the average of the target consumption flows in all time intervals before the second time interval B in the billing period a value, determined as the predicted consumption flow rate of the plurality of users in the second time interval B;

When the second time interval B is one time interval of the first N time intervals in the charging period, and the multiple user identifiers have data traffic in a previous charging period of the charging period When the record is consumed, or when the second time interval B is any time interval after the Nth time interval in the charge period, the target of the N time intervals before the second time interval B The average of the consumption flows is determined as the predicted consumption flow of the plurality of users in the second time interval B:

Wherein, the N is a positive integer, and for any time interval C before the second time interval B, when the plurality of user identifiers have actual consumption flows in the time interval C, the time interval The target consumption flow rate of C refers to the actual consumption flow rate of the plurality of user identifiers in the time interval C, and when the plurality of user identifiers do not have actual consumption flow rate in the time interval C, the time interval The target consumption flow rate of C refers to the predicted consumption flow rate of the plurality of user identifiers in the time interval C.

Optionally, the multiple user identifiers are identifiers of multiple Internet of Things cards that are bound to the target traffic pool and are activated during the charging period, where the target traffic pool refers to any traffic managed by the Internet of Things. Pool.

In the embodiment of the present application, the traffic package and the traffic consumption record corresponding to each user identifier in the multiple user identifiers before the current time point of the charging period may be obtained at any time in the charging period, and then according to the current time point. a traffic consumption record of each user identifier in the user identifier, predicting a sum of consumption flows of the plurality of user identifiers in a billing period, and obtaining a predicted total consumption traffic, according to the predicted total consumption traffic and each user identifier corresponding to the The traffic plan sends the traffic plan adjustment indication information to the charging system of the operator, where the data package adjustment indication information includes at least one user identifier and a corresponding new traffic package of the multiple user identifiers, to indicate that the charging system is The at least one user identifier adjusts the traffic plan to reduce the settlement fee of the plurality of user identifiers and the operator. That is, the total consumption traffic of the plurality of user identifiers in the billing period can be accurately predicted at any time within the billing period, and the traffic plan of the plurality of user identifiers is automatically performed according to the predicted total consumption traffic. The adjustment makes the settlement fee of the current billing cycle minimize. Compared with the artificial adjustment method in the related art, the adjustment method is more timely and more accurate, and the user can further save the settlement fee, and the flexibility is high.

It should be noted that, when the device that adjusts the traffic package for multiple user identifiers in the foregoing embodiment is used to adjust the traffic package of multiple user identifiers, only the division of each functional module is used as an example. In actual applications, The above-mentioned function assignment is completed by different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device for adjusting the traffic package for multiple user identifiers is the same as the method for adjusting the traffic package for multiple user identifiers, and the specific implementation process is not described here.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in accordance with embodiments of the present application are generated in whole or in part. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be from a website site, computer, server or data center Transfer to another website site, computer, server, or data center by wire (eg, coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (eg, infrared, wireless, microwave, etc.). The computer readable storage medium can be any available media that can be accessed by a computer or a data storage device such as a server, data center, or the like that includes one or more available media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a digital versatile disc (DVD)), or a semiconductor medium (for example, a solid state disk (SSD)). )Wait.

A person skilled in the art may understand that all or part of the steps of implementing the above embodiments may be completed by hardware, or may be instructed by a program to execute related hardware, and the program may be stored in a computer readable storage medium. The storage medium mentioned may be a read only memory, a magnetic disk or an optical disk or the like.

The above description of the embodiments of the present application is not intended to limit the embodiments of the present application. Any modifications, equivalent substitutions, improvements, etc., which are included in the spirit and principles of the embodiments of the present application, should be included in Within the scope of protection of the embodiments of the present application.

Claims (12)

1. A method for adjusting a traffic package for a plurality of user identifiers, where the plurality of user identifiers share a number of in-package flows provided by an operator, wherein the method includes:

   Obtaining a data package and a traffic consumption record corresponding to each user identifier of the multiple user identifiers before the current time point of the charging period;

   Determining, according to the traffic consumption record, a sum of consumption flows of the multiple user identifiers in the charging period, and obtaining a predicted total consumption traffic;

   And sending the traffic plan adjustment indication information to the charging system of the operator according to the predicted total consumption traffic and the traffic plan corresponding to each user identifier of the multiple user identifiers, to indicate that the charging system is At least one of the plurality of user identifiers adjusts the traffic plan, so that the settlement fee of the plurality of user identifiers that are settled with the operator according to the adjusted traffic plan in the billing period is less than the traffic according to the adjustment a settlement fee for settlement of the package with the operator, wherein the data package adjustment indication information includes the at least one user identifier and a corresponding new traffic package.
2. The method according to claim 1, wherein the sending the traffic to the charging system of the operator according to the predicted total consumption traffic and a traffic package corresponding to each user identifier of the plurality of user identifiers Package adjustment instructions include:

   And accumulating the amount of the in-package traffic in the data package corresponding to each of the plurality of user identifiers, to obtain the total package traffic;

   Determining a first difference between the predicted total consumption flow and the total package flow;

   And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator.
3. The method according to claim 2, wherein the plurality of user identifiers have different traffic packages;

   And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator, including:

   Determining, when the first difference is greater than or equal to a preset threshold, and the at least one user identifier is the plurality of user identifiers, determining a first ratio between the predicted total consumption traffic and the total package traffic;

   Determining, by any one of the at least one user identifiers A, a product of the number of in-package traffic in the traffic plan corresponding to the user identifier A and the first ratio;

   According to the product, a traffic plan with the smallest difference between the number of traffic in the package and the product is determined as the traffic package of the user identifier A, or from the plurality of traffic packages provided by the operator. In the plurality of traffic packages, determining, by the traffic plan that the number of traffic in the package is greater than or equal to the product, and the difference between the products is the traffic package of the user identifier A, or from the multiple traffic In the package, determining, as the user identifier A, a traffic plan with the minimum settlement tariff between the user identifier A and the operator in the case where the total consumption flow in the billing period is equal to the product Data Package;

   And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.
4. The method according to claim 2, wherein the plurality of user identifiers have the same traffic package;

   And sending, according to the first difference, the data package adjustment indication information to the charging system of the operator, including:

   Determining, between the predicted total consumption flow and the quantity of the at least one user identifier, when the first difference is greater than or equal to a preset threshold and the at least one user identifier is the plurality of user identifiers ratio;

   Determining, between the plurality of traffic packages provided by the operator, between the number of traffic in the package and the second ratio, according to the second ratio, The traffic plan with the smallest difference is used as the new traffic package of the user identifier A, or from the plurality of traffic packages, determining that the amount of traffic in the package is greater than or equal to the second ratio and between the second ratio The traffic plan with the smallest difference is used as the traffic package of the user identifier A, or from the plurality of traffic packages, determining that the total consumption traffic of the user identifier A in the billing period is equal to the first In the case of the second ratio, the traffic plan with the lowest settlement tariff of the operator is used as the new traffic package of the user identifier A;

   And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.
5. The method according to claim 2, wherein the transmitting the data package adjustment indication information to the charging system of the operator according to the first difference comprises:

   Determining, when the first difference is greater than or equal to a preset threshold, a third ratio between the first difference and the number of the at least one user identifier;

   When the predicted total consumption traffic is less than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic plan corresponding to the user identifier A, and the number a second difference between the three ratios;

   Determining, according to the second difference, a traffic plan with the smallest difference between the number of flows in the package and the second difference from the plurality of data packages provided by the operator as the user identifier A a new traffic package, or a traffic plan from the plurality of traffic packages that determines that the amount of traffic in the package is greater than or equal to the second difference and the difference between the second difference is the smallest Identifying a new traffic package of A, or determining, from the plurality of traffic packages, that the total consumption flow of the user identifier A in the charging period is equal to the second difference, and the operation The traffic plan with the lowest settlement tariff between the merchants is used as the new traffic package of the user identifier A;

   And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.
6. The method according to claim 5, wherein after determining the third ratio between the first difference and the number of the at least one user identifier, the method further comprises:

   When the predicted total consumption traffic is greater than the total package traffic, determining, for any one of the at least one user identifiers, the number of in-package traffic in the traffic package corresponding to the user identifier A, and the number The sum between the three ratios;

   Determining, according to the sum of the plurality of data packages provided by the operator, a traffic package having the smallest difference between the number of traffic in the package and the sum value as the new traffic package of the user identifier A, Or determining, from the plurality of data packages, a traffic package whose amount of traffic in the package is greater than or equal to the sum value and having a smallest difference from the sum, as a new traffic package of the user identifier A, or And determining, in the plurality of traffic packages, a traffic plan having a minimum settlement tariff with the operator when the total consumption flow of the user identifier A in the charging period is equal to the sum value The new traffic package of the user identifier A;

   And sending, according to the at least one user identifier and the new traffic package of the at least one user identifier, traffic plan adjustment indication information to the charging system of the operator, to indicate that the charging system identifies the at least one user identifier The traffic plan is adjusted to the corresponding new traffic plan.
7. The method according to any one of claims 1-6, wherein the predicting total consumption of the plurality of user identifiers in the billing period is predicted according to the traffic consumption record Traffic, including:

   Performing statistics on the traffic consumption record to obtain actual consumption traffic of the multiple user identifiers in at least one first time interval, where the at least one first time interval refers to the first time from the charging period At least one time interval from the interval to the target time interval;

   Wherein, when the current time point is the end time of a time interval in the charging period, the target time interval is a time interval in which the current time point is located, and when the current time point is not a time interval in the charging period The end time interval is the latest time interval before the current time point in the billing period;

   Determining, according to actual consumption flows of the plurality of user identifiers in the at least one first time interval, predicted consumption flows of the plurality of user identifiers in at least one second time interval, the at least one second time interval Means at least one time interval after the target time interval in the billing period;

   Adding the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval and the predicted consumption flow rate in the at least one second time interval to obtain the predicted total consumption flow rate.
8. The method according to claim 7, wherein said determining said plurality of user identifiers is at least one second time based on actual consumption flows of said plurality of user identifiers in said at least one first time interval Forecasted consumption flows within the interval, including:

   Determining, according to the actual consumption flow rate of the plurality of user identifiers in the at least one first time interval, a predicted consumption of the plurality of user identifiers in the at least one second time interval by a preset moving average model method flow.
9. The method according to claim 8, wherein the determining the plurality of the actual consumption flows in the at least one first time interval according to the plurality of user identifiers by a preset moving average model method The predicted consumption flow of the user identification in the at least one second time interval includes:

   For any of the at least one second time interval B, when the second time interval B is one of the first N time intervals within the charging period, and the plurality of time intervals When the user ID does not have a data traffic consumption record in the previous billing period of the billing period, the average of the target consumption flows in all time intervals before the second time interval B in the billing period a value, determined as the predicted consumption flow rate of the plurality of users in the second time interval B;

   When the second time interval B is one time interval of the first N time intervals in the charging period, and the multiple user identifiers have data traffic in a previous charging period of the charging period When the record is consumed, or when the second time interval B is any time interval after the Nth time interval in the charge period, the target of the N time intervals before the second time interval B The average of the consumption flows is determined as the predicted consumption flow of the plurality of users in the second time interval B:

   Wherein, the N is a positive integer, and for any time interval C before the second time interval B, when the plurality of user identifiers have actual consumption flows in the time interval C, the time interval The target consumption flow rate of C refers to the actual consumption flow rate of the plurality of user identifiers in the time interval C, and when the plurality of user identifiers do not have actual consumption flow rate in the time interval C, the time interval The target consumption flow rate of C refers to the predicted consumption flow rate of the plurality of user identifiers in the time interval C.
10. The method according to any one of claims 1-9, wherein the plurality of user identifiers are identifiers of a plurality of Internet of Things cards that are bound to a target traffic pool and activated during the billing period, The target traffic pool refers to any traffic pool managed by the Internet of Things.
11. An apparatus for adjusting a traffic package for a plurality of user identifiers, the plurality of user identifiers sharing service traffic provided by an operator, the apparatus comprising a memory, a processor, and being stored on the memory and on the processor A computer program, characterized in that the processor is configured to perform the steps of any of the methods of claims 1-10.
12. A computer readable storage medium having stored therein instructions that, when executed on a computer, cause the computer to perform the method of any of claims 1-10.

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