CN114338429B - Network bandwidth determining method and device and electronic equipment - Google Patents

Abstract

The invention discloses a method and a device for determining network bandwidth and electronic equipment. Relates to the field of financial science and technology, wherein the method comprises the following steps: and acquiring flow data acquired by an Internet access port in a historical time period, and determining second flow data in a future time period and a confidence interval corresponding to the second flow data based on the flow data, so as to determine network bandwidth corresponding to the future time period according to the confidence interval. The invention at least solves the technical problems of inaccurate network bandwidth estimation in the prior art by estimating the network bandwidth demand of the future time period according to the historical experience in a manual mode.

Description

Network bandwidth determining method and device and electronic equipment

Technical Field

The present invention relates to the field of financial science and technology, and in particular, to a method and apparatus for determining network bandwidth, and an electronic device.

Background

With the advent of the internet era, more and more businesses need to be transacted online by relying on the internet in the operation process of enterprises. For example, in the financial industry, the internet is becoming an important ligament for business handling and communication between financial institutions and customers. The internet access line is an entrance for providing internet service for clients by using a financial institution, and has an important role. Thus, the network bandwidth of the internet access line must meet the needs of the financial institution to interact with the customer.

However, because of traffic and time variations, the network bandwidth requirements vary, and therefore, the network bandwidth size needs to be periodically assessed to accommodate the varying network bandwidth requirements. If the estimated network bandwidth is too large, waste is generated, and unnecessary economic loss is generated because network operators usually charge according to the network bandwidth size; if the network bandwidth obtained by evaluation is too small, the requirement of interaction between the financial institution and the customer cannot be met, and more serious business influence and economic influence can be generated.

In addition, in the prior art, the evaluation of the network bandwidth mainly adopts a manual evaluation mode, and the peak value of the flow data in the historical time period is simply analyzed, so that the network bandwidth in the future time period is estimated, for example, the maximum value of the flow data in the historical time period is selected, and the maximum value is multiplied by a preset multiple, so that the network bandwidth in the future time period is estimated.

Disclosure of Invention

The embodiment of the invention provides a method, a device and electronic equipment for determining network bandwidth, which at least solve the technical problem that network bandwidth estimation is inaccurate in the prior art by estimating network bandwidth requirements of a future time period according to historical experience in a manual mode.

According to an aspect of an embodiment of the present invention, there is provided a method for determining a network bandwidth, including: and acquiring flow data acquired by the Internet access port in a historical time period, and determining second flow data in a future time period and a confidence interval corresponding to the second flow data based on the flow data, so as to determine network bandwidth corresponding to the future time period according to the confidence interval.

Further, the method for determining the network bandwidth further comprises the following steps: before acquiring the flow data acquired by the Internet access port in the historical time period, acquiring an accumulated flow value of the Internet access port according to a preset time frequency, wherein the accumulated flow value is used for representing the total flow data passing through the Internet access port at the current moment. And determining flow data of at least one acquisition time according to the accumulated flow value, so as to store the flow data of at least one acquisition time into a preset storage area.

Further, the method for determining the network bandwidth further comprises the following steps: and determining first flow data corresponding to at least one historical subperiod according to the flow data, wherein the historical period comprises at least one historical subperiod. The second flow data and the confidence interval corresponding to the second flow data within the future time period are determined based on the first flow data.

Further, the method for determining the network bandwidth further comprises the following steps: and acquiring flow data acquired in a historical time period from a preset storage area, and dividing the flow data into at least one data set according to the acquisition time of the flow data, wherein each data set corresponds to one historical sub-time period. And sequencing the flow data in at least one data set to obtain a sequencing result, and acquiring target flow data from the at least one data set according to the sequencing result. And determining first flow data according to the target flow data corresponding to each historical sub-time period.

Further, the method for determining the network bandwidth further comprises the following steps: after first flow data corresponding to at least one historical subperiod is determined according to the flow data, a first type date in the historical period is obtained, and the first flow data corresponding to the first type date is updated.

Further, the method for determining the network bandwidth further comprises the following steps: a first date identification of the first type of date is determined, wherein the first date identification is used to characterize an order of the dates in the time period. And determining a second type of date from the historical time period according to the first date identifier, wherein the second type of date and the first type of date have the same first date identifier. And updating the first flow data of the first type of date according to the first flow data of the second type of date to obtain the updated first flow data of the first type of date.

Further, the method for determining the network bandwidth further comprises the following steps: the historical time periods are divided into at least one date set according to the first date identifications, wherein the historical sub-time periods in each date set have the same first date identification. And determining second flow data in a future time period and a confidence interval corresponding to the second flow data according to the first flow data corresponding to the historical sub-time period in each date set.

Further, the method for determining the network bandwidth further comprises the following steps: after determining second flow data and confidence intervals corresponding to the second flow data in a future time period based on the flow data, calculating a first ratio of first data corresponding to each first type of date to second data corresponding to each first type of date in a historical time period, wherein the first data is used for representing the first flow data before updating corresponding to each first type of date, and the second data is used for representing the first flow data after updating corresponding to each first type of date. The first type of date in the history period is determined as at least one first type of date set according to a second date identifier, wherein the second date identifier is used for representing the type of each first type of date, and the first type of date in each first type of date set has the same second date type identifier. According to the first ratio, a second ratio of each first type date set in the historical time period is determined, according to a second date mark of each first type date in the future time period, a target ratio is determined from the second ratio, and further according to the target ratio, second flow data corresponding to each first type date in the future time period and a confidence interval are updated.

Further, the method for determining the network bandwidth further comprises the following steps: dividing at least one future sub-time period from the future time period, acquiring a target confidence interval corresponding to each future sub-time period, determining an upper limit value corresponding to each target confidence interval, acquiring a target upper limit value from at least one upper limit value, and finally determining the target upper limit value as the network bandwidth corresponding to the future time period.

According to another aspect of the embodiment of the present invention, there is also provided a network bandwidth determining apparatus, including: the acquisition module is used for acquiring flow data acquired by the Internet access port in a historical time period; the first determining module is used for determining second flow data and a confidence interval corresponding to the second flow data in a future time period based on the flow data; and the second determining module is used for determining the network bandwidth corresponding to the future time period according to the confidence interval.

According to another aspect of the embodiments of the present invention, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described method of determining a network bandwidth when run.

According to another aspect of the embodiments of the present invention, there is further provided an electronic device, where the electronic device includes one or more processors, and the electronic device further includes a memory, configured to store one or more programs, which when executed by the one or more processors, cause the one or more processors to implement a method for running the program, where the program is configured to perform the above-described method for determining a network bandwidth when running.

In the embodiment of the invention, the second traffic data in the future time period and the confidence interval corresponding to the second traffic data are determined according to the traffic data in the historical time period, and the traffic data acquired by the Internet access port in the historical time period are acquired, so that the second traffic data in the future time period and the confidence interval corresponding to the second traffic data are determined based on the traffic data, and the network bandwidth corresponding to the future time period is determined according to the confidence interval.

As can be seen from the above, by collecting the traffic data at the internet access port, the traffic data in the historical time period can be recorded, so that the traffic data in the historical time period can be selected as a reference when the network bandwidth corresponding to the future time period needs to be estimated. In addition, in the application, the second traffic data and the confidence interval corresponding to the second traffic data in the future time period can be determined based on the traffic data, so that when the traffic data changes along with the time, the second traffic data and the confidence interval corresponding to the second traffic data in the future time period can be determined according to the change trend and the credibility range of the traffic data, the network bandwidth corresponding to the future time period determined based on the confidence interval is more in line with the objective rule of the time change of the traffic data, the technical problem that the network bandwidth demand in the future time period is estimated manually according to the history experience in the prior art, and the inaccurate network bandwidth estimation is realized, the waste effect of the network bandwidth is reduced as much as possible under the condition of ensuring the normal operation of the service, and the improvement of the network bandwidth utilization rate and the saving of the economic cost are facilitated.

Therefore, the scheme provided by the application achieves the aim of accurately estimating the network bandwidth of the future time period, achieves the technical effect of improving the utilization rate of the network bandwidth, and solves the technical problem that the network bandwidth estimation is inaccurate in the prior art by estimating the network bandwidth requirement of the future time period according to the historical experience in a manual mode.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:

FIG. 1 is a flow chart of an alternative method of determining network bandwidth in accordance with an embodiment of the present invention;

FIG. 2 is a schematic diagram of an alternative method of determining network bandwidth according to an embodiment of the invention;

FIG. 3 is a flow chart of an alternative method of determining network bandwidth in accordance with an embodiment of the present invention;

FIG. 4 is a flow chart of an alternative acquisition flow data according to an embodiment of the present invention;

FIG. 5 is a flow chart of an alternative confidence interval for second flow data in accordance with an embodiment of the present invention;

FIG. 6 is a flow chart of an alternative method of determining network bandwidth in accordance with an embodiment of the present invention;

FIG. 7 is a flow chart of an alternative method of determining network bandwidth in accordance with an embodiment of the present invention;

FIG. 8 is a flow chart of an alternative method of determining network bandwidth in accordance with an embodiment of the present invention;

FIG. 9 is a schematic diagram of an alternative network bandwidth determination apparatus according to an embodiment of the present invention;

fig. 10 is a schematic diagram of an alternative electronic device according to an embodiment of the invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In addition, it should be noted that, in the scheme of the embodiment of the present invention, the acquisition, storage, application, etc. of the related user personal information are all information authorized by the user or sufficiently authorized by each party. The electronic device may be used as an execution body of the method for determining the network bandwidth in the embodiment of the present invention, where the electronic device at least includes: desktop computers, notebook computers, smart phones, smart tablets, smart portable wearable devices, and the like.

Example 1

According to an embodiment of the present invention, there is provided an embodiment of a method for determining network bandwidth, it should be noted that the steps illustrated in the flowchart of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.

Fig. 1 is a flowchart of an alternative method for determining network bandwidth according to an embodiment of the present invention, as shown in fig. 1, the method includes the steps of:

and step 101, acquiring flow data acquired by an Internet access port in a historical time period.

In step 101, the internet access port may be a port where an internet access line is connected to a terminal device, where the terminal device may be a network device such as a switch. In addition, the number of the internet access lines can be multiple, and correspondingly, the number of the internet access ports can also be multiple. The traffic data may be divided into output traffic data, which may be traffic data output from an internet device of a financial institution to an external internet device, and input traffic data, which is traffic data input from the external internet device to the internet device of the financial institution, for example. In addition, the historical period of time may be a longer period of time, for example, 3 months or one year, etc.

Optionally, fig. 2 is a schematic diagram of an alternative method for determining a network bandwidth according to an embodiment of the present invention, where, as shown in fig. 2, the network bandwidth may be determined by the following virtual devices: flow acquisition means D001, flow data storage means D002, flow prediction means D003, bandwidth evaluation means D004, visualization means D005, and evaluation bandwidth validation means D006. The traffic acquisition device D001 may be a script, which is configured to acquire traffic data on the internet access line. The flow data storage device D002 may be a preset storage area for storing the flow data collected by the flow collection device D001. The flow prediction device D003 is configured to calculate the second flow data and a confidence interval corresponding to the second flow data according to the historical flow data. The bandwidth evaluation device D004 is configured to calculate the network bandwidth according to the confidence interval. The visualization device D005 is configured to visually display the processed historical traffic data, the second traffic data, the confidence interval, the network bandwidth, and the like. The estimated bandwidth validating means D006 is configured to validate the newly estimated network bandwidth into the existing internet access line.

It should be noted that in the above process, by collecting the traffic data at the internet access port, the effect of recording the traffic data in the historical time period is achieved, so that the traffic data in the historical time period can be selected as the reference data when the network bandwidth corresponding to the future time period needs to be estimated.

Step 102, determining second flow data and a confidence interval corresponding to the second flow data in a future time period based on the flow data.

In step 102, the electronic device may determine, by way of prediction, second traffic data in a future time period and a confidence interval corresponding to the second traffic data, based on the traffic data collected in the historical time period, where the second traffic data may be traffic data that may be required daily in the future time period, for example, when the future time period is one month, the second traffic data may be one traffic data predicted by the electronic device daily in the future one month. It should be noted that, the future time period may be another time period such as half a year, one year, and the like, and the embodiment of the present invention does not limit the duration of the future time period.

It should be noted that, in the above process, because the electronic device may determine the second traffic data and the confidence interval corresponding to the second traffic data in the future time period based on the traffic data, when the traffic data changes with time, the electronic device may determine the second traffic data and the confidence interval corresponding to the second traffic data in the future time period based on the change trend and the trusted range of the traffic data on the basis of the traffic data, so that the network bandwidth corresponding to the future time period determined based on the confidence interval better accords with the objective rule of the traffic data changing with time, thereby realizing the effect of reducing the waste of the network bandwidth as much as possible under the condition of ensuring normal interaction of the service, and being beneficial to improving the utilization rate of the network bandwidth and saving the economic cost.

And step 103, determining the network bandwidth corresponding to the future time period according to the confidence interval.

In step 103, the confidence interval has an upper limit value and a lower limit value, and the confidence of the confidence interval may be adjusted according to the actual requirement of the user, for example, the confidence is set to 60%, and the electronic device has 60% of the flow data grasping the future time period within the confidence interval. In addition, the electronic device may determine the network bandwidth corresponding to the future time period according to the confidence interval, for example, the future time period is one month in the future, and there are 30 days altogether, the electronic device counts the upper limit value of the confidence interval of each day, and selects the maximum upper limit value of 30 days as the network bandwidth corresponding to the future time period, or the electronic device may also select the maximum 5 upper limit values of 30 days, and calculate the average value of the 5 upper limit values as the network bandwidth corresponding to the future time period.

Optionally, fig. 3 is a flowchart of an optional method for determining a network bandwidth according to an embodiment of the present invention, and as shown in fig. 3, an overall flow of the method for determining a network bandwidth includes:

step 301, collecting flow data of an internet access port. The frequency of the electronic device for collecting the flow data can be a preset time frequency, for example, the electronic device is collected every 30 seconds.

Step 302, predicting second flow data and a confidence interval corresponding to the second flow data in a future time period based on the historical flow data. For example, the electronic device may predict daily traffic data for a month in the future and confidence intervals corresponding to the predicted traffic data.

In step 303, the electronic device calculates the network bandwidth according to the confidence interval of the second traffic data.

Step 304, network bandwidth assessment visualization. The electronic device may display traffic data over the historical time period and second traffic data, network bandwidth, for the predicted future time period on a display page. In addition, the display page can also display that the electronic equipment generates a corresponding fitting curve and a confidence interval curve according to the flow data of the historical time period, and predicts the fitting curve and the confidence interval curve according to the second flow data.

Step 305 evaluates the network bandwidth into effect. The electronic device may notify the operator of the estimated network bandwidth and take effect when the next period comes or automatically switch to the estimated network bandwidth by the electronic device directly when the next period comes.

It should be noted that, the network bandwidth corresponding to the future preset time period is determined through the confidence interval, so that the technical problem that the network bandwidth estimation is inaccurate in the prior art by estimating the network bandwidth requirement of the future time period according to the historical experience in a manual mode is solved, and the effect of flexibly controlling the network bandwidth estimation is realized by supporting the user to adjust the confidence according to the actual requirement.

As can be seen from the foregoing, in the embodiment of the present invention, by determining the second traffic data and the confidence interval corresponding to the second traffic data in the future time period according to the traffic data in the historical time period, the traffic data acquired by the internet access port in the historical time period is acquired, and the second traffic data and the confidence interval corresponding to the second traffic data in the future time period are determined based on the traffic data, so that the network bandwidth corresponding to the future time period is determined according to the confidence interval.

As can be seen from the above, the flow data is collected at the internet access port, and the flow data in the historical time period can be recorded, so that the flow data in the historical time period can be selected as the reference data when the network bandwidth corresponding to the future time period needs to be estimated. In addition, in the application, the second traffic data and the confidence interval corresponding to the second traffic data in the future time period can be determined based on the traffic data, so that when the traffic data changes along with the time, the second traffic data and the confidence interval corresponding to the second traffic data in the future time period can be determined according to the change trend and the credibility range of the traffic data, the network bandwidth corresponding to the future time period determined based on the confidence interval is more in line with the objective rule of the time change of the traffic data, the technical problem that the network bandwidth demand in the future time period is estimated manually according to the history experience in the prior art, and the inaccurate network bandwidth estimation is realized, the waste effect of the network bandwidth is reduced as much as possible under the condition of ensuring normal interaction of services, and the improvement of the network bandwidth utilization rate and the saving of economic cost are facilitated.

Therefore, the scheme provided by the application achieves the purpose of accurately estimating the network bandwidth of the future time period, and achieves the technical effect of improving the utilization rate of the network bandwidth.

In an alternative embodiment, before acquiring the flow data acquired by the internet access port in the historical time period, the electronic device may acquire an accumulated flow value of the internet access port according to a preset time frequency, where the accumulated flow value is used to characterize the total flow data passing through the internet access port from the current moment. The electronic device can also determine flow data of at least one collection time according to the accumulated flow value, and finally store the flow data of at least one collection time into a preset storage area.

Optionally, fig. 4 is a flowchart of an alternative flow data acquisition according to an embodiment of the present invention, and as shown in fig. 4, the flow data acquisition includes the following steps:

in step 401, an acquisition script is deployed on an acquisition server. The collection server is a server for collecting flow data, and can be a local server or a cloud server. The acquisition script is a program obtained by programming by a programmer, and it should be noted that the acquisition server needs to implement basic network communication with a network device connected to the internet access line, so as to count flow data.

Step 402, the collection script obtains the accumulated flow value on the internet access port according to the preset time frequency. The preset time frequency may be a relatively small period of time, for example, collected every 30 seconds, so as to ensure accuracy of the collected integrated flow value. In addition, the collection script can obtain the accumulated flow value at the current moment through the simple network management protocol snmp (simple network management protocol) and the MIB value of the flow index.

In step 403, flow data at each acquisition time is calculated. After the electronic device obtains the accumulated flow value, the electronic device calculates the flow data at the current acquisition time by adopting a calculation method of dividing the backward difference by the time interval. The specific calculation process is that the accumulated flow value acquired at present is subtracted from the accumulated flow value acquired at last, the difference obtained by subtracting is divided by the acquired time interval, and the finally obtained calculated value can be recorded as the flow data at the current acquisition time. For example, assuming that the current acquired integrated flow value is 1090 bits, the last acquired integrated flow value is 1030 bits, and the acquisition time interval is 30 seconds, the flow data at the current acquisition time point is (1090-1030)/30=2 bits/second.

And step 404, storing the calculated flow data in a preset storage area. The electronic equipment can store the calculated flow value (namely flow data) of at least one acquisition time into a preset storage area, and when the flow data is stored, the electronic equipment records an internet access line, a circulation direction and the acquisition time corresponding to the flow data. The flow direction may represent whether the traffic data is output traffic data or input traffic data, and may also specifically represent the origin attribution and destination attribution of the traffic data. For example, the electronic device records two pieces of flow data, namely, flow data 1 and flow data 2, and by analyzing the flow directions of the two pieces of flow data, the electronic device can recognize that the flow data 1 is output from the a financial institution to the B financial institution, and the flow data 2 is input from the C company to the a financial institution.

It should be noted that through the above process, the electronic device may count the flow data corresponding to each acquisition time in real time, so as to record the change situation of the flow data along with the change of time, and be favorable for the operator to summarize the rule between the flow data and the time, and further accurately predict the network bandwidth of the future time period according to the rule between the flow data and the time.

In an alternative embodiment, the electronic device may determine first traffic data corresponding to at least one historical sub-period according to the traffic data, where the historical period includes at least one historical sub-period, and determine second traffic data in a future period and a confidence interval corresponding to the second traffic data based on the first traffic data.

Alternatively, the history sub-period may be a period of time in the history period, for example, the history period may be one month or one year, and the history sub-period may be one day corresponding to one month or one year. In addition, the first flow data may be a peak flow data corresponding to the historical sub-period, for example, when the historical sub-period is one day in the historical period, the first flow data may be the maximum flow data in one day, or the flow data collected in one day is sorted according to the size, the first 5 maximum flow data are selected, and the average value is calculated as the first flow data.

By the above process, the first flow data in each historical sub-period is determined from a large amount of flow data collected in the historical time period, so that the effect of simplifying the flow data and determining the flow data peak value in each historical sub-period is realized.

In an optional embodiment, the electronic device may acquire the flow data acquired in the historical time period from the preset storage area, and divide the flow data into at least one data set according to the acquisition time of the flow data, where each data set corresponds to one historical sub-time period, and then sort the flow data in at least one data set to obtain a sorting result, so as to acquire the target flow data from at least one data set according to the sorting result, and determine the first flow data according to the target flow data corresponding to each historical sub-time period.

Optionally, fig. 5 is a flowchart of an optional confidence interval corresponding to the second traffic data according to an embodiment of the present invention, as shown in fig. 5, including the following steps:

step 501, historical traffic data is obtained. The electronic device may obtain the traffic data in the history period from the preset storage area, and the history period may be a longer period, for example, 3 months or 1 year, and the length of the history period is not limited.

At step 502, first flow data for each day in the historical flow is calculated. The first flow data may also be characterized as a peak value of the flow data, and the electronic device may divide the flow data into at least one data set according to a collection time of the flow data, where each data set corresponds to a historical sub-period, for example, in fig. 5, the historical sub-period is one day, and the electronic device divides the flow data of each day into one data set, so that when there are multiple days in the historical period, multiple data sets are obtained. Further, the electronic device sorts the flow data in each data set according to the size, and a sorting result is obtained. In calculating the first flow data per day, the electronic device may take the first m largest flow data as target flow data and calculate an average value of the target flow data. The formula is as follows:

Wherein P is _d The first flow data on the d-th day in the historical flow data is represented, m represents the number of flow data in front of the largest row,maximum traffic data at the ith bit on day d. When there is only one target flow rate data, the maximum value of the daily flow rate data is taken as the first flow rate data.

Step 503, the first traffic data of each day is used as a time sequence. After obtaining the first traffic data, the electronic device may use the historical sub-period and the corresponding first traffic data as a set of time sequences, for example, as shown in fig. 5, each day is used as time, and each peak value corresponding to each time is used as a value corresponding to each day, where the peak value changes with time, and the time sequences are formed.

It should be noted that, through the above-mentioned process, it is realized that the time sequence of the first traffic data is established according to the time variation, so that the effect of determining the trend of the traffic data variation according to the time sequence and improving the accuracy of estimating the network bandwidth of the future time period is realized.

In an alternative embodiment, after determining the first traffic data corresponding to the at least one historical subperiod according to the traffic data, the electronic device may acquire a first type of date in the historical period, and update the first traffic data corresponding to the first type of date.

Alternatively, as in step 504 of fig. 5, the first type of date may be a special date in a historical time period, where the special date may be a holiday such as a national legal holiday or a weekend, in which the traffic data follows a different law than usual, e.g., in a holiday, the business is typically inactive and the traffic data may be small, so the electronic device needs to modify the first traffic data for the first type of date.

In an alternative embodiment, when modifying the first traffic data of the first type, the electronic device may determine a first date identifier of the first type of date, where the first date identifier is used to characterize an order of the dates in the time period, and determine the second type of date from the historical time period according to the first date identifier, where the second type of date has the same first date identifier as the first type of date, so that the first traffic data of the first type of date is updated according to the first traffic data of the second type of date, and the updated first traffic data of the first type of date is obtained.

Alternatively, the first date identifier is used to characterize the order of the dates in a time period, e.g., the time period is one week, and the first date identifier may be the number of weeks, i.e., the days of the week, e.g., monday, etc. The second type of date has the same first date identifier as the first type of date, and is a usual date adjacent to the first type of date, i.e., a non-special date, wherein the second type of date may be selected in plurality according to a preset number.

Optionally, fig. 6 is a flowchart of an alternative method for determining network bandwidth according to an embodiment of the present invention, and as shown in fig. 6, a flow for correcting first traffic data of a first type of date is as follows:

step 601, determining the number of weeks of the first type of date to be corrected.

Step 602, determining a preset number of usual dates adjacent to the same number of weeks as the first type of date to be corrected. If the first type of date to be corrected is not preceded by a usual date of the same number of weeks, then only the usual date of the same number of weeks after the first type of date to be corrected is selected, for example, the special date to be corrected is 10 months 1 day, the number of weeks is tuesday, the preset number is 4, if the history period is selected to be 9 months 30 days to 10 months 30 days, then there is no date of tuesday before 10 months 1 days in the history period, and therefore, as the second type of date, four dates of 10 months 8 days, 10 months 15 days, 10 months 22 days, and 10 months 29 days after 10 months 1 day can be selected.

Further, if the first type of date to be corrected is not followed by a usual date of the same number of weeks, only the usual date of the same number of weeks preceding the first type of date to be corrected is selected as the second type of date. If the regular dates with the same week number are arranged before and after the first type of date to be corrected, the regular dates with the same number are taken as the second type of date before and after; if there is insufficient to take the same number on one side, then after that side is taken out, the remainder is taken on the other side. It should be noted that, when the preset number is odd, a neighboring preset number of usual dates with the same number of weeks as the first type date to be corrected may be selected to be taken more than one side of the first type date to be corrected. In a special case, when the history period is shorter, and therefore, the second type of date satisfying the preset number cannot be selected, all the second type of dates determined in the history period may be directly used to execute step 603, and the preset number does not need to be satisfied.

And 603, taking an average value of the first flow data corresponding to the selected second type of date as the first flow data of the corrected first type of date, namely, updating the first flow data of the first type of date according to the first flow data of the second type of date to obtain the updated first flow data of the first type of date.

It should be noted that, for special dates such as holidays, the special processing is performed through the above process, so that the difference of flow data between the special date and the non-special date can be adapted, thereby being beneficial to improving the prediction accuracy of the network bandwidth.

In an alternative embodiment, the electronic device may divide the historical time period into at least one date set according to the first date identifier, where the historical sub-time periods in each date set have the same first date identifier, and determine the second flow data in the future time period and the confidence interval corresponding to the second flow data according to the first flow data corresponding to the historical sub-time periods in each date set.

Alternatively, as in step 505 of fig. 5, the first flow data per day is logarithmically taken as the value for subsequent operations. In fig. 5, the preset sub-period is one day.

Step 506, grouping the dates of the history data by the number of weeks. It is known from the foregoing that, in step 506, the first date identifier may be a day of the week, which is a day of the week. The electronic device may divide the traffic data of the same number of weeks into one group, such as by monday into the same group, by friday into the same group, etc., 7 groups in total, i.e., divide the historical time period into at least one date set according to the first date identifier, wherein the historical sub-time periods in each date set have the same first date identifier.

In step 507, a time series model is built in each set of data. In step 507, the time series model may be a differential autoregressive moving average model, and the training data of the time series model may be a peak value of each day in each set of data, that is, the first flow data corresponding to the historical subperiod in each date set, and when the training data is used to train the model, the user may set a selection range of parameters of the time series model, for example, use an information standard to select super parameters of the time series model.

Step 508 predicts daily second flow data and confidence intervals for a future period of time for each group. The future period of time is a future period of time, and the length of the future period of time may be selected according to the needs of the user, for example, one month. The daily peak value and the confidence interval thereof are confidence intervals corresponding to the second flow data of each day and the second flow data in a preset time period in the future, the second flow data of each day and the confidence intervals corresponding to the second flow data are output by a time sequence model, wherein the output form of the confidence intervals is an upper limit value and a lower limit value of the confidence interval, the confidence of the confidence interval can be adjusted according to requirements, for example, 60% of confidence can be selected, which means that 60% of the held second flow is in the confidence interval.

Step 509, performing an exponential operation on the confidence interval corresponding to the second flow data to restore the range of values before taking the logarithm.

Step 510, merging the prediction results of all groups. The daily peak values and the confidence intervals of the daily peak values which are respectively predicted by each week group are combined together to form every second flow data in the continuous future time period and the confidence intervals corresponding to the second flow data. For example, according to the first date identifier, the historical time period is divided into 7 date sets, namely, a monday group, a tuesday group and a sunday group, wherein the monday group comprises 3 days, according to the first flow data corresponding to each day in 3 days, the second flow data of monday corresponding to the future time period and the confidence interval of the second flow data can be predicted through a time sequence model, for example, 4 mondays in the future time period, and the time sequence model can output 4 confidence intervals of the second flow data and the second flow data.

In step 511, the prediction result of the first type date is adjusted. In this case, since a special date, i.e., a second type date, may also exist in the future time period, the electronic device may also need to adjust the second traffic data corresponding to the special date and the confidence interval corresponding to the second traffic data.

In an alternative embodiment, the electronic device calculates a first ratio of first data corresponding to each first type of date to second data in the history period after determining the second flow data and the confidence interval corresponding to the second flow data in the future period based on the flow data, wherein the first data is used for characterizing the first flow data before update corresponding to each first type of date, the second data is used for characterizing the first flow data after update corresponding to each first type of date, and the first type of date in the history period is determined as at least one first type of date set according to the second date identifier, wherein the second date identifier is used for characterizing the type of each first type of date, the second type of date in each first type of date set has the same second date type identifier, thereby determining a second ratio of each first type of date set in the history period according to the first ratio, determining a target ratio from the second ratio according to the second date identifier of each first type of date in the future period, and further determining the first type of date set in the history period according to the second ratio, and the confidence interval corresponding to each first type of date in the future period.

Optionally, fig. 7 is a flowchart of an alternative method for determining network bandwidth according to an embodiment of the present invention, and as shown in fig. 7, a flow for adjusting a prediction result of a first type of date is as follows:

in step 701, a first ratio of the first data to the second data corresponding to each first type of date in the historical time period is calculated.

Step 702, determining a first type of date in the historical time period as at least one first type of date set according to the second date identification. For example, the non-weekends in legal holidays are a first type of date set, and the weekends in legal holidays are a first type of date set originally on weekends because the weekends that require work for legal holiday tuning are a first type of date set.

Step 703, determining a second ratio for each first type of date set in the historical time period based on the first ratios. For each set of first type dates, the electronic device may calculate an average of the first ratios of all first type dates in the set and take the average as the second ratio of the set.

Step 704, determining a second date identification in the future time period based on each of the first type dates in the future time period, and determining a target ratio from the second ratio. I.e. a first type of date set in which a first type of date is located in a future time period.

Step 705, updating the second traffic data and the confidence interval corresponding to each first type date in the future time period according to the target ratio. The second flow data corresponding to each first type date in the future time period is multiplied by the target ratio to be used as updated second flow data, and the confidence interval is multiplied by the target ratio to be used as updated confidence interval.

Through the process, more accurate prediction is realized on the flow data corresponding to the special date in the future time period, so that the network bandwidth prediction accuracy of the whole future time period is improved.

In an alternative embodiment, the electronic device may divide at least one future sub-period from the future period, and obtain a target confidence interval corresponding to each future sub-period, so as to determine an upper limit value corresponding to each target confidence interval, and obtain a target upper limit value from at least one upper limit value, so as to determine that the target upper limit value is a network bandwidth corresponding to the future period.

Optionally, fig. 8 is a flowchart of an optional method for determining a network bandwidth according to an embodiment of the present invention, as shown in fig. 8, a flow for calculating a network bandwidth according to a confidence interval is as follows:

Step 801, a length of a future time period is determined. I.e. how long in the future the required bandwidth is to be assessed.

Step 802, obtaining an upper limit value of a confidence interval of the second flow data of each day within a corresponding length of the future time period.

In step 803, the maximum value of the obtained upper limit values is calculated as the network bandwidth.

It should be noted that in the above process, the confidence interval under the appropriate confidence is selected according to the confidence requirement by using the confidence interval principle to evaluate the network bandwidth, which is more scientific, so as to realize the effect of more accurate network bandwidth prediction.

As can be seen from the above, in the solution provided by the embodiment of the present invention, by collecting the traffic data at the internet access port, the effect of recording the traffic data in the historical time period is achieved, so that the traffic data in the historical time period can be selected as a reference when the network bandwidth corresponding to the future time period needs to be estimated. In addition, because the second flow data and the confidence interval corresponding to the second flow data in the future time period can be determined based on the flow data in the scheme of the embodiment of the invention, when the flow data changes along with the time, the confidence interval corresponding to the second flow data in the future time period can be determined based on the flow data according to the change trend and the trusted range of the flow data, so that the network bandwidth corresponding to the future time period determined based on the confidence interval better accords with the objective rule of the change of the flow data along with the time, the technical problem that the network bandwidth estimation is inaccurate in the prior art due to the fact that the network bandwidth demand of the future time period is estimated according to the historical experience in a manual mode is solved, and the effects of reducing the waste of the network bandwidth, improving the utilization rate of the network bandwidth and saving the economic cost as much as possible under the condition of ensuring normal interaction of the service are realized.

Therefore, according to the scheme provided by the embodiment of the invention, the purpose of improving the accuracy of estimating the network bandwidth of the future time period is achieved, the technical effect of improving the utilization rate of the network bandwidth is achieved, and the technical problem that the network bandwidth estimation is inaccurate in the prior art by estimating the network bandwidth requirement of the future time period according to the historical experience in a manual mode is solved.

Example 2

There is further provided an embodiment of a network bandwidth determining apparatus according to an embodiment of the present invention, where fig. 9 is a schematic diagram of an alternative network bandwidth determining apparatus according to an embodiment of the present invention, as shown in fig. 9, and the apparatus includes: the acquisition module 901 is used for acquiring flow data acquired by the internet access port in a historical time period; a first determining module 902, configured to determine second traffic data and a confidence interval corresponding to the second traffic data in a future time period based on the traffic data; a second determining module 903 is configured to determine a network bandwidth corresponding to the future time period according to the confidence interval.

It should be noted that the above-mentioned obtaining module 901, the first determining module 902, and the second determining module 903 correspond to steps 101 to 103 in the above-mentioned embodiment, and the three modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the above-mentioned embodiment 1.

Optionally, the network bandwidth determining device further includes: the device comprises an acquisition module, a third determination module and a storage module. The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring an accumulated flow value of an Internet access port according to a preset time frequency, and the accumulated flow value is used for representing total flow data passing through the Internet access port from the current moment; the third determining module is used for determining flow data of at least one acquisition moment according to the accumulated flow value; the storage module is used for storing the flow data of at least one acquisition time into a preset storage area.

Optionally, the first determining module further includes: and a fourth determination module and a fifth determination module. The fourth determining module is used for determining first flow data corresponding to at least one historical subperiod according to the flow data, wherein the historical period comprises at least one historical subperiod; and a fifth determining module, configured to determine second flow data and a confidence interval corresponding to the second flow data in a future time period based on the first flow data.

Optionally, the fourth determining module further includes: the device comprises a first acquisition module, a division module, a sequencing module, a second acquisition module and a sixth determination module. The first acquisition module is used for acquiring flow data acquired in a historical time period from a preset storage area; the dividing module is used for dividing the flow data into at least one data set according to the acquisition time of the flow data, wherein each data set corresponds to one historical sub-time period; the sequencing module is used for sequencing the flow data in at least one data set to obtain a sequencing result; the second acquisition module is used for acquiring target flow data from at least one data set according to the sequencing result; and the sixth determining module is used for determining the first flow data according to the target flow data corresponding to each historical sub-time period.

Optionally, the network bandwidth determining device further includes: and the third acquisition module and the updating module. The third acquisition module is used for acquiring a first type date in the historical time period; and the updating module is used for updating the first flow data corresponding to the first type date.

Optionally, the update module further includes: a seventh determination module, an eighth determination module, and a first update module. Wherein the seventh determining module is configured to determine a first date identifier of a first type of date, where the first date identifier is used to characterize an order of the dates in the time period; an eighth determining module, configured to determine a second type of date from the historical time period according to the first date identifier, where the second type of date has the same first date identifier as the first type of date; the first updating module is used for updating the first flow data of the first type date according to the first flow data of the second type date to obtain the updated first flow data of the first type date.

Optionally, the fifth determining module further includes: the first division module and the ninth determination module. The first dividing module is used for dividing the historical time period into at least one date set according to the first date mark, wherein the historical sub-time period in each date set has the same first date mark; and the ninth determining module is used for determining second flow data in a future time period and a confidence interval corresponding to the second flow data according to the first flow data corresponding to the historical sub-time period in each date set.

Optionally, the network bandwidth determining device further includes: the device comprises a computing module, a tenth determining module, an eleventh determining module, a twelfth determining module and a second updating module. The computing module is used for computing a first ratio of first data corresponding to each first type date and second data corresponding to each first type date in the historical time period, wherein the first data are used for representing the first flow data before updating corresponding to each first type date, and the second data are used for representing the first flow data after updating corresponding to each first type date; a tenth determining module, configured to determine, according to a second date identifier, a first type date in the historical time period as at least one first type date set, where the second date identifier is used to characterize a type of each first type date, and the first type dates in each first type date set have the same second date type identifier; an eleventh determining module for determining a second ratio for each first type of date set in the historical time period based on the first ratios; a twelfth determination module for determining a target ratio from the second ratio based on the second date identification for each of the first type dates in the future time period; and the second updating module is used for updating the second flow data corresponding to each first type date in the future time period and the confidence interval according to the target ratio.

Optionally, the second determining module further includes: the device comprises a second dividing module, a fourth acquiring module, a thirteenth determining module, a fifth acquiring module and a fourteenth determining module. Wherein the second dividing module is used for dividing at least one future sub-time period from the future time period; a fourth obtaining module, configured to obtain a target confidence interval corresponding to each future sub-time period; a thirteenth determining module, configured to determine an upper limit value corresponding to each target confidence interval; a fifth acquisition module for acquiring a target upper limit value from the at least one upper limit value; and the fourteenth determining module is used for determining the target upper limit value as the network bandwidth corresponding to the future time period.

Example 3

According to an embodiment of the present invention, there is further provided an embodiment of an electronic device, where fig. 10 is a schematic diagram of an alternative electronic device according to an embodiment of the present invention, and as shown in fig. 10, the electronic device includes a processor, a memory, and a program stored on the memory and executable on the processor, and when the processor executes the program, the following steps are implemented by the processor:

and acquiring flow data acquired by the Internet access port in a historical time period, and determining second flow data in a future time period and a confidence interval corresponding to the second flow data based on the flow data, so as to determine network bandwidth corresponding to the future time period according to the confidence interval.

Before acquiring the flow data acquired by the Internet access port in the historical time period, acquiring an accumulated flow value of the Internet access port according to a preset time frequency, wherein the accumulated flow value is used for representing the total flow data passing through the Internet access port until the current moment, and determining the flow data of at least one acquisition moment according to the accumulated flow value, so that the flow data of at least one acquisition moment is stored in a preset storage area.

And determining first flow data corresponding to at least one historical sub-time period according to the flow data, wherein the historical time period comprises at least one historical sub-time period, so that second flow data in a future time period and a confidence interval corresponding to the second flow data are determined based on the first flow data.

The method comprises the steps of obtaining flow data collected in a historical time period from a preset storage area, dividing the flow data into at least one data set according to the collection time of the flow data, sequencing the flow data in the at least one data set to obtain a sequencing result, obtaining target flow data from the at least one data set according to the sequencing result, and determining first flow data according to the target flow data corresponding to each historical time period.

After first flow data corresponding to at least one historical subperiod is determined according to the flow data, a first type date in the historical period is obtained, and the first flow data corresponding to the first type date is updated.

Determining a first date identifier of a first type of date, wherein the first date identifier is used for representing the sequence of the dates in the time period, determining a second type of date from the historical time period according to the first date identifier, wherein the second type of date and the first type of date have the same first date identifier, and accordingly updating the first flow data of the first type of date according to the first flow data of the second type of date to obtain updated first flow data of the first type of date.

And dividing the historical time period into at least one date set according to the first date identifications, wherein the historical sub-time periods in each date set have the same first date identification, so that the second flow data in the future time period and the confidence interval corresponding to the second flow data are determined according to the first flow data corresponding to the historical sub-time periods in each date set.

After determining second flow data and confidence intervals corresponding to the second flow data within a future time period based on the flow data, calculating a first ratio of first data corresponding to each first type of date to second data within the history time period, wherein the first data is used for representing the first flow data before updating corresponding to each first type of date, the second data is used for representing the first flow data after updating corresponding to each first type of date, then determining the first type of date in the history time period as at least one first type of date set according to a second date identifier, wherein the second date identifier is used for representing the type of each first type of date, the first type of date in each first type of date set has the same second date type identifier, thereby determining a second ratio of each first type of date set in the history time period according to the first ratio, determining a target ratio from the second ratio according to the second date identifier of each first type of date in the future time period, and updating the second type of date corresponding to each second type of date in the future time period and confidence interval according to the target ratio.

Dividing at least one future sub-time period from the future time period, acquiring a target confidence interval corresponding to each future sub-time period, determining an upper limit value corresponding to each target confidence interval, acquiring a target upper limit value from at least one upper limit value, and finally determining the target upper limit value as the network bandwidth corresponding to the future time period.

The electronic device herein may be a server, a cell phone, a tablet, a computer, etc.

Example 4

According to an embodiment of the present invention, there is also provided a computer-readable storage medium in which a computer program is stored, wherein the computer program is configured to perform the method for determining a network bandwidth in embodiment 1 described above when run.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of units may be a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims (6)

1. A method for determining a network bandwidth, comprising:

acquiring flow data acquired by an Internet access port in a historical time period;

determining second flow data in a future time period and a confidence interval corresponding to the second flow data based on the flow data;

determining a network bandwidth corresponding to the future time period according to the confidence interval;

before acquiring the flow data acquired by the internet access port in the historical time period, the method comprises the following steps:

collecting an accumulated flow value of the Internet access port according to a preset time frequency, wherein the accumulated flow value is used for representing total flow data passing through the Internet access port from the current moment;

determining flow data of at least one acquisition moment according to the accumulated flow value;

storing the flow data of the at least one acquisition moment into a preset storage area;

Wherein determining second flow data and a confidence interval corresponding to the second flow data in a future time period based on the flow data comprises:

determining first flow data corresponding to at least one historical sub-period according to the flow data, wherein the historical period comprises the at least one historical sub-period;

determining second flow data in the future time period and a confidence interval corresponding to the second flow data based on the first flow data;

wherein after determining first traffic data corresponding to at least one historical sub-period according to the traffic data, the method further comprises:

acquiring a first type date in the historical time period;

updating first flow data corresponding to the first type date;

wherein updating the first flow data corresponding to the first type of date includes:

determining a first date identifier of the first type of date, wherein the first date identifier is used for representing the sequence of the dates in the time period;

determining a second type of date from the historical time period according to the first date identifier, wherein the second type of date and the first type of date have the same first date identifier;

Updating the first flow data of the first type date according to the first flow data of the second type date to obtain the updated first flow data of the first type date;

wherein determining second flow data and a confidence interval corresponding to the second flow in the future time period based on the first flow data comprises:

dividing the historical time period into at least one date set according to the first date mark, wherein the historical sub-time periods in each date set have the same first date mark;

determining second flow data in the future time period and a confidence interval corresponding to the second flow data according to the first flow data corresponding to the historical sub-time period in each date set;

wherein after determining second flow data and a confidence interval corresponding to the second flow data within a future time period based on the flow data, the method further comprises:

calculating a first ratio of first data corresponding to each first type of date to second data corresponding to each first type of date in the historical time period, wherein the first data is used for representing pre-update first flow data corresponding to each first type of date, and the second data is used for representing updated first flow data corresponding to each first type of date;

Determining the first type date in the history time period as at least one first type date set according to a second date identifier, wherein the second date identifier is used for representing the type of each first type date, and the first type dates in each first type date set have the same second date type identifier;

determining a second ratio for each first type of date set in the historical time period from the first ratio;

determining a target ratio from the second ratio based on a second date identification for each first type of date in the future time period;

and updating the second flow data corresponding to each first type date in the future time period and the confidence interval according to the target ratio.

2. The method for determining network bandwidth according to claim 1, wherein determining first traffic data corresponding to at least one historical sub-period according to the traffic data comprises:

acquiring flow data acquired in the historical time period from the preset storage area;

dividing the flow data into at least one data set according to the acquisition time of the flow data, wherein each data set corresponds to a historical sub-time period;

Sequencing the flow data in the at least one data set to obtain a sequencing result;

acquiring target flow data from the at least one data set according to the sequencing result;

and determining the first flow data according to the target flow data corresponding to each historical sub-time period.

3. The method for determining a network bandwidth according to claim 1, wherein determining a network bandwidth corresponding to the future time period according to the confidence interval comprises:

dividing at least one future sub-time period from the future time period;

acquiring a target confidence interval corresponding to each future sub-time period;

determining an upper limit value corresponding to each target confidence interval;

obtaining a target upper limit value from at least one of the upper limit values;

and determining the target upper limit value as the network bandwidth corresponding to the future time period.

4. A network bandwidth determining apparatus, comprising:

the acquisition module is used for acquiring flow data acquired by the Internet access port in a historical time period;

the first determining module is used for determining second flow data in a future time period and a confidence interval corresponding to the second flow data based on the flow data;

A second determining module, configured to determine a network bandwidth corresponding to the future time period according to the confidence interval;

the acquisition module is used for acquiring the accumulated flow value of the Internet access port according to the preset time frequency, wherein the accumulated flow value is used for representing the total flow data passing through the Internet access port from the current moment; the third determining module is used for determining flow data of at least one acquisition moment according to the accumulated flow value; the storage module is used for storing the flow data of at least one acquisition moment into a preset storage area;

wherein the first determining module further comprises: a fourth determining module and a fifth determining module, where the fourth determining module is configured to determine, according to the flow data, first flow data corresponding to at least one historical sub-period, where the historical period includes at least one historical sub-period; a fifth determining module, configured to determine second flow data and a confidence interval corresponding to the second flow data in a future time period based on the first flow data;

wherein, the network bandwidth determining device further comprises: the system comprises a third acquisition module and an updating module, wherein the third acquisition module is used for acquiring a first type date in a historical time period; the updating module is used for updating the first flow data corresponding to the first type date;

Wherein the update module further comprises: the device comprises a seventh determining module, an eighth determining module and a first updating module, wherein the seventh determining module is used for determining a first date identifier of a first type of date, and the first date identifier is used for representing the sequence of the date in a time period; an eighth determining module, configured to determine a second type of date from the historical time period according to the first date identifier, where the second type of date has the same first date identifier as the first type of date; the first updating module is used for updating the first flow data of the first type date according to the first flow data of the second type date to obtain the updated first flow data of the first type date;

wherein the fifth determination module further comprises: the device comprises a first dividing module and a ninth determining module, wherein the first dividing module is used for dividing the historical time period into at least one date set according to a first date identifier, and the historical sub-time period in each date set has the same first date identifier; a ninth determining module, configured to determine, according to the first flow data corresponding to the historical sub-time period in each date set, second flow data in a future time period and a confidence interval corresponding to the second flow data;

Wherein, the network bandwidth determining device further comprises: the system comprises a calculation module, a tenth determination module, an eleventh determination module, a twelfth determination module and a second updating module, wherein the calculation module is used for calculating a first ratio of first data corresponding to each first type date to second data in a historical time period, wherein the first data are used for representing pre-update first flow data corresponding to each first type date, and the second data are used for representing updated first flow data corresponding to each first type date; a tenth determining module, configured to determine, according to a second date identifier, a first type date in the historical time period as at least one first type date set, where the second date identifier is used to characterize a type of each first type date, and the first type dates in each first type date set have the same second date type identifier; an eleventh determining module for determining a second ratio for each first type of date set in the historical time period based on the first ratios; a twelfth determination module for determining a target ratio from the second ratio based on the second date identification for each of the first type dates in the future time period; and the second updating module is used for updating the second flow data corresponding to each first type date in the future time period and the confidence interval according to the target ratio.

5. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program, wherein the computer program is arranged to perform the network bandwidth determination method of any of the claims 1 to 3 at run-time.

6. An electronic device, the electronic device comprising one or more processors; a memory for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement a method for running a program, wherein the program is configured to perform the method of determining network bandwidth of any of claims 1 to 3 when run.