CN111147395B - Network resource adjusting method and device - Google Patents
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Abstract
The embodiment of the invention discloses a network resource adjusting method and device, and relates to the technical field of internet. The problem that in the prior art, due to the fact that the priority of the user service cannot be adjusted in time, the appropriate QoS parameters cannot be matched for the user is solved. The method comprises the following steps: the network resource adjusting device firstly acquires the complaint weight of each preset QoS parameter interval in a first preset time period; then, predicting service use conditions of the first user in a second preset time period of the current date to determine at least one target service; the second preset time period of the current date is positioned after the current moment; determining the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs; further determining the grade of the target service; and then, according to the grade of the target service, adjusting the QoS parameter of the target service in a second preset time period of the current date. The embodiment of the invention is applied to a network system.
Description
Technical Field
The embodiment of the invention relates to the technical field of internet, in particular to a network resource adjusting method and device.
Background
In order to meet the requirements of users for different application with different service qualities, the network needs to allocate and schedule resources according to the requirements of the users, and provide different quality of service (QoS) for different data flows. With the diversification of services and the difference of user preferences, a fixed QoS guarantee template cannot be suitable for all users, and network resource adjustment needs to be performed according to the requirements of the users, so as to configure appropriate QoS parameters for the users. However, the conventional network resource adjustment method is too rigid, and cannot adjust the priority of the user service in time according to the user requirement, so that an appropriate QoS parameter cannot be matched for the user, thereby causing the hysteresis of network resource adjustment and reducing the service experience of the user.
Disclosure of Invention
The invention provides a network resource adjusting method and a network resource adjusting device, which effectively solve the problem that in the prior art, due to the fact that the priority of user services cannot be adjusted in time, appropriate QoS parameters cannot be matched for users.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, a network resource adjusting method is provided, in which a network resource adjusting apparatus first obtains a complaint weight of each preset QoS parameter interval in a first preset time period; for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used for representing the proportion of the complaint data of the preset QoS parameter interval to the total complaint data of the preset QoS parameter interval in a first preset time period; the ending time of the first preset time period is before the current time; then, predicting service use conditions of the first user in a second preset time period of the current date to determine at least one target service; the second preset time period of the current date is positioned after the current moment; determining the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs; further determining the grade of the target service; and then, according to the grade of the target service, adjusting the QoS parameter of the target service in a second preset time period of the current date.
Based on the method, because the problem that the prior art cannot timely adjust the priority of the service according to the requirement of the user is considered, the invention firstly obtains one or more target services which are most likely to be used by the user in a second preset time period of the current date in a prediction mode, and determines the weight of each target service by combining the complaint weight of each preset QoS parameter interval in the first preset time period so as to obtain the corresponding grade of the target service, thereby timely adjusting the QoS parameters of the target service in the second preset time period of the current date according to the grade. Therefore, the network resource is adjusted in advance, and when the user uses the target service which is adjusted by the network resource in the second preset time period of the current date, the network is smoother, so that the service experience of the user is improved.
In a second aspect, a network resource adjusting apparatus is provided, which includes: the obtaining unit is used for obtaining the complaint weight of each preset QoS parameter interval in a first preset time period; for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used for representing the proportion of the complaint data of the preset QoS parameter interval to the total complaint data of the preset QoS parameter interval in a first preset time period; the ending time of the first preset time period is positioned before the current time; the processing unit is used for predicting the service use condition of the first user in a second preset time period of the current date so as to determine at least one target service; the second preset time period of the current date is positioned after the current moment; the processing unit is further used for determining the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs; the processing unit is also used for determining the grade of the target service according to the weight of each target service; and the processing unit is further used for adjusting the QoS parameter of the target service in a second preset time period of the current date according to the grade of the target service.
It can be understood that, the network resource adjusting apparatus is configured to execute the method corresponding to the first aspect provided above, and therefore, the beneficial effects that can be achieved by the network resource adjusting apparatus may refer to the beneficial effects of the method corresponding to the first aspect and the corresponding scheme in the following detailed description, which are not described herein again.
In a third aspect, a network resource adjusting device is provided, where the structure of the network resource adjusting device includes a processor, and the processor is configured to execute program instructions, so that the network resource adjusting device executes the method of the first aspect.
In a fourth aspect, a computer readable storage medium is provided, having stored therein computer program code which, when run on a network resource adjusting apparatus, causes the network resource adjusting apparatus to perform the method of the first aspect described above.
In a fifth aspect, there is provided a computer program product having stored thereon the computer software instructions for causing a network resource adjusting device to execute a program of the method of the first aspect when the computer software instructions are run on the network resource adjusting device.
Drawings
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic system structure diagram of a home gateway application scenario provided in an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a network resource adjusting apparatus according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a network resource adjustment method according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating a method for adjusting network resources according to another embodiment of the present invention;
fig. 5 is a schematic structural diagram of another network resource adjusting apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
It should be noted that in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "such as" in an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present relevant concepts in a concrete fashion.
It should be noted that, in the embodiments of the present invention, "of", "corresponding" and "corresponding" may be sometimes used in combination, and it should be noted that, when the difference is not emphasized, the intended meaning is consistent.
Because the traditional network resource adjusting method is too rigid, the priority of the user service cannot be adjusted in time according to the requirements of the user, so that proper QoS parameters cannot be matched for the user, the hysteresis of network resource adjustment is caused, and the service experience of the user is reduced. The embodiment of the invention provides a network resource adjusting method and a device; the network resource adjusting device acquires one or more target services which are most likely to be used by a user in a second preset time period of the current date in advance in a prediction mode, and determines the weight of each target service by combining the complaint weight of each preset QoS parameter interval in the first preset time period so as to obtain the corresponding grade of the target service, thereby adjusting the QoS parameters of the target service in the second preset time period of the current date in time according to the grade. The problem that in the prior art, due to the fact that the priority of user services cannot be adjusted in time, appropriate QoS parameters cannot be matched for users is solved.
For example, the network resource adjusting apparatus according to the present invention may be as shown in the system structure diagram of a home gateway application scenario in fig. 1, where the system includes a home gateway device 10, a home gateway device 11, a terminal 20 and a terminal 21 connected to the home gateway device 10, and a terminal 22, a terminal 23 and a terminal 24 connected to the home gateway device 11. The home gateway device 10 is an end device of the operator network in the home, is located at the center of the user home network, and is responsible for connecting and managing the service terminals 20 in the home. Generally, one home gateway can control a plurality of terminals.
Here, the system architecture and the service scenario described in the embodiment of the present invention are for more clearly illustrating the technical solution of the embodiment of the present application, and do not constitute a limitation to the technical solution provided in the embodiment of the present application, and it can be known by a person skilled in the art that the technical solution provided in the embodiment of the present application is also applicable to similar technical problems along with the evolution of the network architecture and the appearance of a new service scenario.
For example, in the embodiment of the present application, the home gateway device in fig. 1 is taken as an example, and the home gateway device may specifically be the network resource adjusting apparatus shown in fig. 2, or may also be a device including the network resource adjusting apparatus shown in fig. 2 (for example, the network resource adjusting apparatus is a system on chip/system on chip of the home gateway device). Fig. 2 is a schematic composition diagram of a network resource adjusting device according to an embodiment of the present disclosure, where the network resource adjusting device may be used to implement the network resource adjusting method according to the embodiment of the present disclosure.
As shown in fig. 2, the network resource adjusting apparatus includes a processor 21, and optionally, a memory 22 connected to the processor 21 through a communication bus 24.
In the embodiment of the present application, the processor 21 is a control center of the network resource adjusting apparatus, and may be a single processor or a collective name of multiple processing elements. For example, the processor 21 is a Central Processing Unit (CPU), and may be an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as: one or more Digital Signal Processors (DSPs), or one or more field-programmable gate arrays (FPGAs).
The processor 21 may execute various functions of the network resource adjusting apparatus by running or executing a software program stored in the memory 22 and calling data stored in the memory 22.
For one embodiment, processor 21 may include one or more CPUs, such as CPU 0 and CPU 1 shown in FIG. 2.
For one embodiment, the network resource adjusting apparatus may further include another processor, such as the processor 25 shown in fig. 2, and the processor 25 includes the CPU 0. Each of the plurality of processors in the network resource adjusting apparatus may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
In the embodiment of the present application, the memory 22 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a Random Access Memory (RAM) or other types of dynamic storage devices that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.
In a possible implementation, the memory 22 may exist separately from the processor 21, i.e. the memory 22 may be a memory external to the processor 21, in which case the memory 22 may be connected to the processor 21 via a communication bus 24 for storing instructions or program code. The processor 21, when calling and executing the instructions or program codes stored in the memory 22, can implement the network resource adjustment method provided in the following embodiments of the present application.
In another possible implementation, the memory 22 may also be integrated with the processor 21, that is, the memory 22 may be an internal memory of the processor 21, for example, the memory 22 is a cache memory and may be used for temporarily storing some data and/or instruction information and the like.
Optionally, the network resource adjusting apparatus further includes a communication interface 23.
The communication interface 23 is used to communicate with other devices or communication networks using any transceiver or the like, such as ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), and the like. The communication interface 23 may include a receiving unit implementing a receiving function, and a transmitting unit implementing a transmitting function.
In the embodiment of the present application, the communication bus 24 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (enhanced Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 2, but it is not intended that there be only one bus or one type of bus.
It is noted that the device structure shown in fig. 2 does not constitute a limitation of the network resource adjustment apparatus, which may comprise more or less components than those shown in fig. 2, or some components in combination, or a different arrangement of components, in addition to those shown in fig. 2.
The network resource adjustment method provided in the embodiment of the present application is specifically described below with reference to fig. 1 and fig. 2. Optionally, names of the messages or names of the parameters in the messages in the following embodiments of the present application are only examples, and other names may also be used in specific implementations, and this is not specifically limited in the embodiments of the present application.
Fig. 3 is a schematic flowchart of a network resource adjusting method provided in an embodiment of the present application, and is applied to a network resource adjusting device, where in the following adjusting method example, the network resource adjusting device is used to execute the method, and the network resource adjusting device may be a home gateway device or a chip in the home gateway device or a plug-in the home gateway device, as shown in fig. 3, the adjusting method may include:
301. the network resource adjusting device obtains the complaint weight of each preset QoS parameter interval in a first preset time period.
Specifically, for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used to represent a proportion of complaint data of the preset QoS parameter interval to total complaint data of a first preset time period; the end time of the first preset time period is before the current time.
Illustratively, the QoS parameters of the embodiments of the present invention may include latency, network rate, and traffic type. In addition, the implementation manners of the preset QoS parameter interval, which take time delay, network rate, and service type as examples, are shown in table 1.
TABLE 1
In a specific implementation manner, the network resource adjusting device calculates, by using the obtained first number of times of use, the first duration of use, and the first complaint record of the QoS parameter of the at least one second service used by each second user in each preset QoS parameter interval, complaint data of the at least one second service used by each second user, and counts all the complaint data to generate total complaint data of the first preset time period; meanwhile, complaint data of the preset QoS parameter interval are calculated through the obtained second using times, second using duration and second complaint records of the QoS parameters of at least one second service used by all second users in each preset QoS parameter interval; and then, the network resource adjusting device acquires the complaint weight of each preset QoS parameter interval in the first preset time period according to the ratio of the complaint data of the preset QoS parameter interval to the total complaint data of the first preset time period.
For example, in combination with the interval division condition in table 1, the embodiment of the present application describes, by taking a QoS parameter as an example, an obtaining process of the complaint weight of each preset QoS parameter interval. Acquiring n parts of user data in a first preset time period, wherein the j-th part of user data comprises 5 services used by a user j in the first preset time period, and the time delays corresponding to the 5 services are 35, 90, 120, 200 and 300 in sequence; the service time corresponding to each time delay is 30s, 100s, 200s, 10s and 50 s; the complaint condition corresponding to each time delay is complaint, non-complaint, complaint and non-complaint in turn. Then, by combining the preset time delay interval in table 1, it can be known that the first use frequency in the interval of 0ms to 50ms is 1; the first use times of 50ms-100ms is 1; the first using times of 100ms-500ms is 3; the first use time of 500ms-1s is 0; the first number of uses greater than 1s is 0. The first use duration in the interval 0ms-50ms is 30; the first use time of 50ms-100ms is 100; the first using time of 100ms-500ms is 260; the first use time of 500ms-1s is 0; the first number of uses greater than 1s is 0. Supposing that complaints exist in each preset QoS interval, setting the complaint record as 3; if there is no complaint, the complaint record is 1. And (3) calculating the data according to the following formula (1) to obtain complaint data of the user using 5 services:
Wherein X represents complaint data of each second user using at least one second service (e.g., complaint data of user j using 5 services is complaint data of one of the second users using at least one second service); f. of1Representing a first number of uses; s1Indicating a complaint record; t is t1Representing a first usage duration; i belongs to (0, m), and m represents the number of preset QoS parameter intervals (in combination with table 1, m is 5); j ∈ (0, n), n denotes the number of user data.
And (3) combining the calculation result of the formula (1), counting the 100 parts of user data according to a formula (2) to generate total complaint data Y of a first preset time period:
in addition, complaint data of the preset QoS parameter interval is calculated according to formula (3):
wherein Z represents complaint data of a preset QoS parameter interval; f. of2Representing a first number of uses; s2Indicating a complaint record; t is t2Indicating a first usage period. Finally, by ZiThe ratio to Y determines the complaint weight for the ith preset QoS parameter interval.
It should be noted that the QoS parameters include not only the delay, but also the network rate, the service type, and the like, and the calculation manner of the complaint weights of the preset QoS parameter intervals corresponding to the QoS parameters such as the network rate, the service type, and the like is all the same as the complaint weights of the preset QoS parameter intervals corresponding to the delay, and details are not repeated here.
302. The network resource adjusting device predicts the service use condition of the first user in a second preset time period of the current date to determine at least one target service.
Wherein the second preset time period of the current date is after the current time.
Optionally, the network resource adjusting apparatus may determine, by using a clustering algorithm, service usage of the acquired duration and times of the first user using the at least one first service in the current time period and the historical preset time period, within a second preset time period of the current date, so as to determine the at least one target service.
The current time period is positioned before and adjacent to a second preset time period of the current date; the historical preset time period includes at least a second preset time period of the historical date.
For example, the first service is divided into five categories, i.e., game, video, voice, download, and text browsing, but the category of the first service is not limited herein, and only the above five first services are exemplified. Assuming that the second preset time period of the current date to be predicted is the service usage of the first user at 12 hours and 14 hours of the day, then, considering the continuity of the service, the first service and the duration (of course, there is no limitation on the time period) used by the first user at 10 hours to 12 hours of the day, 12 hours and 14 hours of the last day, need to be obtained, whether the first services of five categories of games, videos, voices, downloads and text browsing are used in the time period, and the duration of using each first service is respectively counted.
For example, a manner of obtaining the duration and the number of times that the first user uses at least one first service in the current time period and the historical preset time period is shown in table 2:
TABLE 2
| Serial | Key index | |
| 1 | Whether the service is used in the current time period | |
| 2 | The service usage time length in the current time period | |
| 3 | Whether the service is used in the second preset time period of yesterday | |
| 4 | The service use time length of the second preset time period yesterday | |
| 5 | Whether the service is used in the second preset time period on the same day of the last week | |
| 6 | The service use time length of the second preset time period on the same day of the last week |
Defining feature vector F in table 2 as { F1, F2, F3, F4, F5, F6 }; wherein, the F1 vector represents whether the service is used in the current time period (assuming that the service is used as 1 and not used as 0), the F2 vector represents the time length (not used as 0) used by the service in the current time period, the F3 vector represents whether the service is used in the second preset time period of yesterday, the F4 vector represents the time length (not used as 0) used by the service in the second preset time period of yesterday, the F5 vector represents whether the service is used in the second preset time period of the same last week, and the F6 vector represents the time length used by the service in the second preset time period of the same last week Degree (0 when not used). For
Indicating whether the first service i is used for the current time period,
wherein,
indicating the length of time used by the first service i in the current time slot, and so on.
In combination with the upper-segment content, a K-means clustering algorithm in a machine learning algorithm is adopted to model the duration and the times of using at least one first service by the first user in the current time segment and the historical preset time segment; if an X-Y binary vector table is established, wherein the X axis is the times and the Y axis is the duration. For any first service, setting X ═ aF1+ bF3+ cF5 and Y ═ aF2+ bF4+ cF6, wherein F1, F3 and F5 take {0 and 1}, namely that the used value is 1 and the unused value is 0; f2, F4 and F6 take the values of 0-300 (according to the collection and statistics once every 5 minutes), abc is a non-0 natural number, all the numbers can be 1 in the initial stage, and the influence proportion of the three time periods on the second preset time period can be gradually adjusted in the later stage according to the improvement of the precision (the influence proportion of the three time periods on the second preset time period is obtained by adjusting the abc value). Here, let K be 3, i.e. the service occurrence frequency is divided into high, medium and low possibility, for example, {0, 0} low possible initial preset aggregation point is specified, {1.5, 450} medium possible initial preset aggregation point, and {3, 900} high possible initial preset aggregation point performs K-means clustering algorithm on the duration and number of times that the first user uses at least one first service in the current time period and the historical preset time period. And taking the obtained high-possibility service as the target service of the second preset time period of the current date.
303. And the network resource adjusting device determines the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs.
It should be noted that, for each target service, the weight of each QoS parameter in the target service is determined; and determining the weight of the target service according to the sum of the weights of each QoS parameter.
That is, it is determined to which preset QoS parameter interval the QoS parameter corresponding to the target service belongs, and then the complaint weight of the preset QoS parameter interval is taken as the weight of the target service.
304. And the network resource adjusting device determines the grade of the target service according to the weight of each target service.
Exemplarily, for each target service, assuming that the included QoS parameter is assumed to have a delay, a network rate and a service type, determining that the delay, the network rate and the service type of the target service all correspond to a preset delay interval, a preset network rate interval and a preset service type interval to which the target service belongs; and then correspondingly acquiring the complaint weight of the preset delay interval, the complaint weight of the preset network rate interval and the complaint weight of the preset service type interval of the target service, and then adding the complaint weights to the complaint weight of the preset network rate interval and the complaint weight of the preset service type interval to acquire the weight of the target service.
305. And the network resource adjusting device adjusts the QoS parameters of the target service in a second preset time period of the current date according to the grade of the target service.
With reference to fig. 3, as shown in fig. 4, the specific implementation manner of step 301 includes steps 401 and 405.
The method comprises the following specific steps:
401. the network resource adjusting device obtains a first use frequency, a first use duration and a first complaint record of a QoS parameter of at least one second service used by each second user in each preset QoS parameter interval in at least one second user in a first preset time period.
402. And the network resource adjusting device calculates the complaint data of each second user using at least one second service according to the first using times, the first using time length and the first complaint record, and counts all the complaint data to generate total complaint data of a first preset time period.
403. And the network resource adjusting device acquires the second using times, the second using time length and the second complaint record of the QoS parameters of at least one second service used by all the second users in each preset QoS parameter interval.
404. And the network resource adjusting device calculates the complaint data of the preset QoS parameter interval according to the second using times, the second using time and the second complaint record.
405. The network resource adjusting device obtains the complaint weight of each preset QoS parameter interval in the first preset time period according to the ratio of the complaint data of the preset QoS parameter interval to the total complaint data of the first preset time period.
In summary, in view of the problem that the prior art cannot adjust the priority of the service in time according to the requirement of the user, in the embodiment of the present application, first, one or more target services that are most likely to be used by the user in the second preset time period of the current date are obtained in a prediction manner, and the weight of each target service is determined in combination with the complaint weight of each preset QoS parameter interval in the first preset time period, so as to obtain the corresponding level of the target service, and thus, the QoS parameter of the target service in the second preset time period of the current date is adjusted in time according to the level. Therefore, by adjusting the network resources in advance, when the user uses the target service which is adjusted by the network resources in the second preset time period of the current date, the network is smoother, and the service experience of the user is improved.
The embodiment of the present invention may perform the division of the function modules on the network resource adjusting apparatus according to the method embodiment, for example, each function module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the embodiment of the present invention is schematic, and is only one logic function division, and another division manner may be available in actual implementation.
As shown in fig. 5, a schematic structural diagram of a network resource adjusting device 50 according to an embodiment of the present invention is shown:
an obtaining unit 501, configured to obtain a complaint weight of each preset QoS parameter interval in a first preset time period; for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used for representing the proportion of the total complaint data of the preset QoS parameter interval in a first preset time period; the ending time of the first preset time period is before the current time.
A processing unit 502, configured to predict service usage of the first user in a second preset time period of a current date, so as to determine at least one target service; the second preset time period of the current date is after the current time.
The processing unit 502 is further configured to determine a weight of each target service according to a QoS parameter interval to which a QoS parameter corresponding to each target service belongs.
The processing unit 502 is further configured to determine a level of the target service according to the weight of each target service.
The processing unit 502 is further configured to adjust a QoS parameter of the target service in a second preset time period of the current date according to the level of the target service.
In an exemplary scheme, the obtaining unit 501 is specifically configured to obtain, in at least one second user in a first preset time period, a first number of times of using, a first duration of using, and a first complaint record of a QoS parameter of at least one second service used by each second user in each preset QoS parameter interval.
The processing unit 502 is configured to calculate, according to the first number of times of use, the first duration of use, and the first complaint record acquired by the acquiring unit 501, complaint data of at least one second service used by each second user, and count all the complaint data to generate total complaint data in a first preset time period.
The obtaining unit 501 is further configured to obtain a second number of times of using, a second duration of using, and a second complaint record of the QoS parameters of at least one second service used by all second users in each preset QoS parameter interval.
The processing unit 502 is configured to calculate complaint data of the preset QoS parameter interval according to the second number of times of use, the second duration of use, and the second complaint record obtained by the obtaining unit 501.
The processing unit 502 is further configured to obtain a complaint weight of each preset QoS parameter interval in the first preset time period according to a ratio of complaint data of the preset QoS parameter interval to total complaint data of the first preset time period.
In an exemplary scheme, the obtaining unit 501 is specifically configured to obtain a duration and a number of times that a first user uses at least one first service in a current time period and a historical preset time period; the current time period is positioned before and adjacent to the second preset time period; the historical preset time period comprises at least one second preset time period of the historical date.
The processing unit 502 is configured to determine, by using a clustering algorithm, service usage in a second preset time period of the current date according to the duration and the number of times of the at least one first service acquired by the acquiring unit 501, so as to determine at least one target service.
In an exemplary scheme, the processing unit 502 is specifically configured to, for each target service, determine a weight of each QoS parameter in the target service; and determining the weight of the target service according to the sum of the weights of each QoS parameter.
All relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and the function thereof is not described herein again.
Of course, the network resource adjusting apparatus 50 provided in the embodiment of the present invention includes, but is not limited to, the above modules, for example, the network resource adjusting apparatus 50 may further include the storage unit 503. The storage unit 503 may be used to store the program code of the network resource adjusting apparatus 50, and may also be used to store data generated by the network resource adjusting apparatus 50 during operation, such as data in a write request.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A method for adjusting network resources, comprising:
obtaining a complaint weight of each preset QoS parameter interval in a first preset time period; for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used for representing the proportion of the complaint data of the preset QoS parameter interval in the total complaint data of the first preset time period; the ending time of the first preset time period is positioned before the current time;
predicting service use conditions of the first user in a second preset time period of the current date to determine at least one target service; a second preset time period of the current date is after the current time;
determining the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs;
determining the grade of the target service according to the weight of each target service;
According to the grade of the target service, adjusting a QoS parameter of the target service in a second preset time period of the current date;
the obtaining of the complaint weight of each preset QoS parameter interval in the first preset time period specifically includes:
acquiring a first use frequency, a first use duration and a first complaint record of a QoS parameter of at least one second service used by each second user in each preset QoS parameter interval in at least one second user in a first preset time period;
calculating complaint data of at least one second service used by each second user according to the first using times, the first using duration and the first complaint record, and counting all the complaint data to generate total complaint data of the first preset time period;
acquiring a second use frequency, a second use duration and a second complaint record of the QoS parameters of at least one second service used by all second users in each preset QoS parameter interval;
calculating complaint data of the preset QoS parameter interval according to the second using times, the second using duration and the second complaint record;
obtaining the complaint weight of each preset QoS parameter interval in a first preset time period according to the ratio of the complaint data of the preset QoS parameter interval to the total complaint data of the first preset time period;
The determining the weight of each target service according to the QoS parameter interval to which the QoS parameter corresponding to each target service belongs specifically includes:
for each target service, determining a QoS parameter interval to which each QoS parameter in the target service belongs, taking the complaint weight of the QoS parameter interval as the weight of the QoS parameter, and determining the weight of the target service according to the sum of the weights of each QoS parameter.
2. The method according to claim 1, wherein the predicting service usage of the first user in a second preset time period of a current date to determine at least one target service specifically comprises:
acquiring the duration and the times of using at least one first service by the first user in the current time period and the historical preset time period; wherein the current time period is before and adjacent to the second preset time period of the current date; the historical preset time period comprises at least one second preset time period of historical date;
and determining the service use condition of the at least one first service in a second preset time period of the current date by using a clustering algorithm according to the duration and the times of the at least one first service so as to determine the at least one target service.
3. A network resource adjustment apparatus, comprising:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring the complaint weight of each preset QoS parameter interval in a first preset time period; for each preset QoS parameter interval, the complaint weight of the preset QoS parameter interval is used for representing the proportion of the complaint data of the preset QoS parameter interval in the total complaint data of the first preset time period; the ending time of the first preset time period is positioned before the current time;
the processing unit is used for predicting the service use condition of the first user in a second preset time period of the current date so as to determine at least one target service; a second preset time period of the current date is after the current time;
the processing unit is further configured to determine a weight of each target service according to a QoS parameter interval to which a QoS parameter corresponding to each target service belongs;
the processing unit is further configured to determine a level of the target service according to the weight of each target service;
the processing unit is further configured to adjust a QoS parameter of the target service within a second preset time period of the current date according to the level of the target service;
The obtaining unit is specifically configured to obtain, in at least one second user in a first preset time period, a first number of times of using, a first using duration, and a first complaint record of a QoS parameter of at least one second service used by each second user in each preset QoS parameter interval;
the processing unit is configured to calculate complaint data of at least one second service used by each second user according to the first number of times of use, the first length of use, and the first complaint record acquired by the acquiring unit, and count all the complaint data to generate total complaint data of the first preset time period;
the obtaining unit is further configured to obtain a second number of times of using, a second duration of using, and a second complaint record of the QoS parameter of at least one second service used by all second users in each preset QoS parameter interval;
the processing unit is configured to calculate complaint data of the preset QoS parameter interval according to the second number of times of use, the second length of time of use, and the second complaint record obtained by the obtaining unit;
the processing unit is further configured to obtain a complaint weight of each preset QoS parameter interval in a first preset time period according to a ratio of the complaint data of the preset QoS parameter interval to the total complaint data of the first preset time period;
The processing unit is specifically configured to, for each target service, determine a QoS parameter interval to which each QoS parameter in the target service belongs, use a complaint weight of the QoS parameter interval as a weight of the QoS parameter, and determine the weight of the target service according to a sum of the weights of each QoS parameter.
4. The network resource adjustment apparatus according to claim 3, comprising:
the acquiring unit is specifically configured to acquire a duration and a number of times that the first user uses at least one first service in a current time period and a historical preset time period; wherein the current time period is before and adjacent to the second preset time period; the historical preset time period comprises at least one second preset time period of historical date;
the processing unit is configured to determine, by using a clustering algorithm, a service usage condition within a second preset time period of the current date according to the duration and the number of times of the at least one first service acquired by the acquiring unit, so as to determine the at least one target service.
5. A network resource adjustment device, characterized in that the structure of the network resource adjustment device comprises a processor, and the processor is used to execute program instructions to make the network resource adjustment device execute the network resource adjustment method according to any one of claims 1-2.
6. A computer-readable storage medium, having stored thereon computer program code which, when run on a network resource adjusting apparatus, causes the network resource adjusting apparatus to execute the network resource adjusting method according to any one of claims 1-2.
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| CN112532346A (en) * | 2020-11-03 | 2021-03-19 | 广州技象科技有限公司 | Link self-adaption method and device based on user time requirement |
| CN112312566B (en) * | 2020-11-18 | 2024-02-02 | 中国联合网络通信集团有限公司 | Communication method, device and system |
| CN113467227A (en) * | 2021-06-30 | 2021-10-01 | 北京达佳互联信息技术有限公司 | Resource delivery method, device, server and storage medium |
| CN114286447B (en) * | 2021-12-27 | 2024-08-02 | 中国联合网络通信集团有限公司 | Scheduling priority adjustment method, equipment and storage medium |
| CN114726922B (en) * | 2022-03-31 | 2023-11-21 | 联想(北京)有限公司 | Network resource scheduling method and device, electronic equipment and storage medium |
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