CN114258055A - Traffic pattern determination method, electronic device, and storage medium - Google Patents
Traffic pattern determination method, electronic device, and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of communication, and particularly discloses a traffic pattern determining method, electronic equipment and a storage medium. The method comprises the following steps: determining a pre-estimated flow value corresponding to the current moment according to historical flow information; respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment; and determining a target flow mode corresponding to the current moment from the flow mode set according to the pre-estimated flow value and a preset flow value corresponding to each flow mode in the flow mode set. The method and the device can provide more flexible network traffic service.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a traffic pattern determining method, an electronic device, and a storage medium.
Background
The fifth generation mobile communication technology (5G,5th generation mobile networks) improves the data throughput rate of the network through three channels of more frequency spectrums, higher frequency spectrum efficiency and denser networking, and meanwhile, the fifth generation mobile communication technology can provide a network slicing technology with customized capability aiming at different user requirements, and can meet the differentiated requirements of the vertical industry in a targeted manner, and different network slices correspond to different network traffic modes. However, the existing network slice technology generally corresponds to one network slice for one class of users, that is, the class of users fixedly use the network traffic mode corresponding to the network slice, and this way is not flexible enough to guarantee the traffic service of users in a cell when the traffic service of the cell changes, and sometimes even affects the user experience.
Disclosure of Invention
The application provides a traffic pattern determination method, an electronic device and a storage medium, which can provide more flexible network traffic service.
In a first aspect, the present application provides a traffic pattern determining method, including:
determining a pre-estimated flow value corresponding to the current moment according to historical flow information;
respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment;
and determining a target flow mode corresponding to the current moment from the flow mode set according to the pre-estimated flow value and a preset flow value corresponding to each flow mode in the flow mode set.
In a second aspect, the present application further provides an electronic device comprising a memory and a processor; the memory is used for storing a computer program; the processor is configured to execute the computer program and to implement the flow pattern determination method as described above when executing the computer program.
In a third aspect, the present application also provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement the flow pattern determination method as described above.
The application discloses a traffic pattern determination method, an electronic device and a storage medium, wherein the method comprises the following steps: determining a pre-estimated flow value corresponding to the current moment according to historical flow information; respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment; and determining a target flow mode corresponding to the current moment from the flow mode set according to the estimated flow value and a preset flow value corresponding to each flow mode in the flow mode set. According to the embodiment of the application, the pre-estimated flow value is determined, the first flow value which is possibly required to be used by a user at the current moment can be determined according to the pre-estimated flow value and the preset flow value actually provided by each flow mode, a more appropriate flow mode is selected from the flow mode set in a self-adaptive mode to serve as the target flow mode, when the flow service of a cell changes, the flow use experience of the user is guaranteed, the waste of the first flow value can be avoided, and more flexible network flow service can be provided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a traffic pattern determination method provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of another traffic pattern determination method provided in the embodiment of the present application;
fig. 3 is a block diagram schematically illustrating a structure of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all embodiments of the present application. 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 application.
The flow diagrams depicted in the figures are merely illustrative and do not necessarily include all of the elements and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
It is to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
The embodiment of the application provides a traffic pattern determination method, electronic equipment and a storage medium. Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic flow chart of a traffic pattern determining method according to an embodiment of the present application, and as shown in fig. 1, the traffic pattern determining method specifically includes steps S101 to S103.
S101, determining an estimated flow value corresponding to the current moment according to historical flow information.
The historical traffic information may include a first traffic value actually used by the user at each time in the past historical time interval, where the first traffic value actually used by the user at each time depends on the network behavior of the user at the time, for example, the user is performing a download operation at one time, the download speed is 10 megabytes per second (Mbps), and the first traffic value actually used by the user at the current second is 10 megabytes per second.
The base station sets a flow mode for each user, each flow mode has a corresponding preset flow value, and the first flow value actually used by the user at each moment generally does not exceed the preset flow value corresponding to the flow mode set by the user given by the operator. For example, the preset traffic value is 10 mbytes per second, and the first traffic value actually used by the user at each time is at most 10 mbytes per second, the user may be a user accessing the same network slice, and the number of users may be one or more.
The first flow value actually used by the user at each past moment can be determined according to the historical flow information, and then the usage habits of the first flow value of the user can be determined, for example, the usage habits of the first flow value of some users are higher, and the usage habits of the flow of some users are lower, and then the first flow value possibly used at the current moment can be predicted according to the historical flow information to serve as the predicted flow value.
S102, respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment.
The traffic mode set may be a traffic mode corresponding to a network slice preset by the base station, different network slices correspond to different traffic modes, and the corresponding network slices may be configured according to the internet access requirements of different users, that is, network services in the corresponding traffic modes may be provided for the users.
The flow pattern set may include a plurality of flow patterns, each flow pattern has a preset flow value corresponding to the preset flow pattern, and the preset flow value may be a first flow value that can be used by a user at most at each time. The preset flow value of the flow mode may be a fixed value, that is, the preset flow value may be a non-fixed value regardless of the time, and may change with the time.
And respectively determining the preset flow value corresponding to each flow mode at the current moment, wherein if the preset flow value corresponding to one flow mode is a fixed value, the preset flow value corresponding to the current moment is the fixed value, and if the preset flow value corresponding to one flow mode can change along with the moment, the preset flow value at the current moment can be determined.
In an embodiment, the traffic pattern set includes a proportional guarantee scheduling pattern and a rate guarantee scheduling pattern, and the operation of respectively determining the preset traffic value corresponding to each traffic pattern included in the traffic pattern set may be implemented as follows:
determining a total first flow value corresponding to the current moment, and determining the product of a preset proportion and the total first flow value as a preset flow value of a proportion guarantee scheduling mode; and determining a preset flow value of the rate guarantee scheduling mode according to the preset rate flow.
The total first traffic value may be a first traffic value divided for an area, the area includes a plurality of users, and the total first traffic value may be a sum of preset traffic values of all users in the area. The total first traffic value may change with the time, so that the total first traffic value at the current time is determined, and the total first traffic value may be divided by the base station, so that the total first traffic value corresponding to the current time may be directly obtained.
For example, the area may be a cell, and the cell includes a plurality of users, each having a respective predetermined flow value. The total first traffic value of the area may be changed by the influence of external factors, so that the preset traffic value of the user in the area may be changed. For example, when the channel quality is good, the total first traffic value of the area may reach 1000 mbytes per second, and the users in the area use the total first traffic value of 1000 mbytes per second together, and when the channel quality is poor, the total first traffic value of the area may be only 500 mbytes per second, so that the users in the area can use only 500 mbytes per second together, and the preset traffic value of the users may also change.
The ratio guarantee scheduling mode may be a flow mode in which the first flow value corresponding to the preset ratio is determined from the total first flow value as the preset flow value according to the preset ratio. Therefore, after the total first flow value at the current moment is determined, the product of the preset proportion and the total first flow value is determined as the preset flow value of the proportion guarantee scheduling mode. For example, if the total first traffic value is 1000 megabytes per second and the preset proportion is 10%, the preset traffic value corresponding to the proportion guarantee scheduling mode is 100 megabytes per second; and if the total first flow value is 500 megabytes per second, the preset flow value corresponding to the proportional guarantee scheduling mode is 50 megabytes per second.
The rate guarantee scheduling mode may be a traffic mode that uses a fixed preset rate traffic as a preset traffic value, and the rate guarantee scheduling mode is independent of the total first traffic value, and thus, the preset rate traffic may be determined as the preset traffic value of the rate guarantee scheduling mode. For example, if the preset rate traffic of the rate guarantee scheduling mode is 80 mbytes per second, the preset traffic value of the rate guarantee scheduling mode is 80 mbytes per second at any time.
S103, determining a target flow rate mode corresponding to the current moment from the flow rate mode set according to the estimated flow rate value and a preset flow rate value corresponding to each flow rate mode in the flow rate mode set.
The estimated flow value represents a first flow value which may be needed by a user at the current moment, and the preset flow value corresponding to each flow mode in the flow mode set represents an upper limit of the first flow value which can be provided for the user by each flow mode.
When the first flow value actually required to be used by the user is higher, if a lower preset flow value is provided, normal use of the user may be affected. When the first traffic value required to be used by the user is low, if a higher preset traffic value is provided, the first traffic value may be wasted, and the first traffic values of other users in the same area may be crowded.
Therefore, a more appropriate flow rate mode can be determined from the flow rate mode set according to the estimated flow rate value and the preset flow rate value corresponding to each flow rate mode in the flow rate mode set, and the flow rate mode is used as a target flow rate mode corresponding to the current moment. After the target traffic mode corresponding to the current time is determined, the base station may configure a network slice corresponding to the target traffic mode for the user, and further provide a preset traffic value corresponding to the target traffic mode for the user.
In an embodiment, the operation of determining the target flow rate mode corresponding to the current time from the flow rate mode set according to the estimated flow rate value and the preset flow rate value corresponding to each flow rate mode included in the flow rate mode set may be implemented in the following manner:
and determining a target flow rate mode corresponding to the current moment from the flow rate mode set according to the ratio of the pre-estimated flow rate value to the preset flow rate value corresponding to each flow rate mode in the flow rate mode set.
According to the ratio of the pre-estimated flow value to the pre-set flow value corresponding to each flow mode in the flow mode set, which pre-set flow values of the flow modes are larger than the pre-estimated flow value and which pre-set flow values are smaller than the pre-estimated flow value can be determined, and then the flow mode corresponding to the appropriate pre-estimated flow value can be selected as the target flow mode.
According to the method and the device, the pre-estimated flow value is determined, the first flow value which is possibly required to be used by the user at the current moment can be determined according to the pre-estimated flow value and the preset flow value actually provided by each flow mode, a more appropriate flow mode is selected from the flow mode set to serve as the target flow mode, when the flow service of the cell changes, the flow use experience of the user is guaranteed, the waste of the first flow value can be avoided, and more flexible network flow service can be provided.
In an embodiment, the operation of determining the target flow rate mode corresponding to the current time from the flow rate mode set according to the ratio of the pre-estimated flow rate value to the preset flow rate value corresponding to each flow rate mode included in the flow rate mode set may be implemented as follows:
if the estimated flow value is larger than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the largest preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is smaller than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the minimum preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is not greater than the preset flow values corresponding to all the flow modes included in the flow mode set, or the estimated flow value is not less than the preset flow values corresponding to all the flow modes included in the flow mode set, determining the flow mode corresponding to the preset flow value greater than the estimated flow value in the preset flow values corresponding to each flow mode as the target flow mode corresponding to the current moment.
If the estimated flow value is greater than the preset flow value corresponding to each flow mode in the flow mode set, that is, the estimated first flow value that the user may need to use at the current time is particularly high, and the preset flow values corresponding to all the flow modes in the flow mode set are all smaller than the estimated flow value, so that the flow mode corresponding to the maximum preset flow value in the flow mode set is selected as the target flow mode, and the influence on the network flow use experience of the user is reduced as much as possible.
If the estimated flow value is smaller than the preset flow value corresponding to each flow mode in the flow mode set, that is, the estimated first flow value that the user may need to use at the current time is lower, the preset flow values corresponding to all the flow modes in the flow mode set are all larger than the estimated flow value, and any flow mode can meet the use requirement of the user, so that the flow mode corresponding to the minimum preset flow value in the flow mode set is selected as the target flow mode, which can avoid waste of flow caused by the adoption of a higher preset flow value, and the saved first flow value can be used by other users in the area, so that the total first flow value in the area can be more reasonably distributed, and the spectrum utilization efficiency is improved.
And if the estimated flow value is not greater than the preset flow values corresponding to all the flow modes included in the flow mode set, or if the estimated flow value is not less than the preset flow values corresponding to all the flow modes included in the flow mode set, that is, if there are preset flow values corresponding to a plurality of flow modes included in the flow mode set, there are more than the estimated flow value and there are also less than the estimated flow value. If the preset flow value smaller than the estimated flow value is selected, normal use of the user can be influenced, so that the flow mode corresponding to the preset flow value larger than the estimated flow value is selected and used as the target flow mode, and normal use of the user can be guaranteed.
If the flow mode set comprises three or more flow modes and the flow modes with the preset flow values larger than the estimated flow values comprise two or more flow modes, the flow mode with the minimum preset flow value in the flow modes corresponding to the preset flow values larger than the estimated flow values can be selected as the target flow mode. If the flow mode set only comprises two flow modes, the flow mode corresponding to the preset flow value larger than the estimated flow value can be directly selected as the target flow mode.
Exemplarily, it is assumed that the traffic pattern set includes a proportional guarantee scheduling pattern and a rate guarantee scheduling pattern, and the preset traffic value of the proportional guarantee scheduling pattern is yproportionThe preset flow value of the rate guarantee scheduling mode is yrateThe estimated flow value is yfilter。
At yfilterGreater than yproportionAnd y isfilterGreater than yrateWhen y is inproportionGreater than yrateDetermining the proportion guarantee scheduling mode as the target flow mode corresponding to the current moment, and if yproportionLess than yrateAnd determining the rate guarantee scheduling mode as a target flow mode corresponding to the current moment.
At yfilterGreater than yproportionAnd y isfilterLess than yrateAnd if so, determining the rate guarantee scheduling mode as the target traffic mode corresponding to the current moment.
At yfilterLess than yproportionAnd y isfilterGreater than yrateAnd if so, determining the proportional guarantee scheduling mode as a target flow mode corresponding to the current moment.
At yfilterLess than yproportionAnd y isfilterLess than yrateWhen y is inproportionGreater than yrateDetermining the rate guarantee scheduling mode as the target traffic mode corresponding to the current time, and if yproportionLess than yrateAnd determining the proportional guarantee scheduling mode as a target flow mode corresponding to the current moment.
In an embodiment, as shown in fig. 2, the operation of determining the estimated flow value corresponding to the current time according to the historical flow information may be implemented as follows:
s201, determining a time flow relation according to historical flow information, wherein the time flow relation is a relation between each time and a first flow value corresponding to each time.
The historical traffic information may include a first traffic value actually used by the user at each historical time in the past historical time interval, that is, the historical traffic information includes a plurality of historical times and first traffic values corresponding to the plurality of historical times. Each user has a specific network habit, so that the historical time and the first flow value corresponding to the historical time have a certain relationship, and therefore, a relational expression of each time and the first flow value corresponding to each time can be determined according to historical flow information and is used as a time flow relational expression. Illustratively, the historical first flow values may be analyzed according to a linear regression method to determine a time-of-day flow relationship.
S202, determining a first flow value corresponding to the current time according to the time flow relation, and determining an estimated flow value corresponding to the current time according to the first flow value corresponding to the current time.
The time flow relation expresses a relation between each time and the first flow value corresponding to each time, so that the first flow value corresponding to the current time can be determined according to the time flow relation, and further the estimated flow value can be determined. For example, a first flow rate value corresponding to the current time determined according to the time-flow rate relational expression may be used as the estimated flow rate value.
In one embodiment, the operation of determining the time flow relation according to the historical flow information may be implemented as follows:
determining historical moments included in the historical traffic information and a first traffic value corresponding to each historical moment; determining the historical time and the corresponding coordinate position of the first traffic numerical value corresponding to each historical time in a preset coordinate system; and fitting according to the coordinate position to obtain a fitting equation, and determining the fitting equation as a time flow relational expression.
The preset coordinate system may be established by taking the time as an abscissa and the first flow value as an ordinate. And a coordinate position can be determined in the coordinate system according to each historical time and the corresponding first flow value, and a plurality of coordinate positions can be determined in the preset coordinate system according to a plurality of historical times and the corresponding first flow values of the plurality of historical times.
Fitting is to determine a smooth line from the plurality of points, which line can connect the plurality of points. A fitting equation for a plurality of coordinate positions can be determined from the fitting, a smooth line can be determined from the plurality of coordinate positions, and the line can connect the plurality of coordinate positions, in one case, all of which are located on the line, and in another case, some of the plurality of coordinate positions are located on the line, and the other observation points are kept relatively close to the line. For example, the line may be a curved line or a straight line.
The fitting equation obtained through fitting can embody the functional relationship between the time and the first flow value, and further is used for predicting the first flow value corresponding to the current time.
In one embodiment, the operation of fitting according to the coordinate positions to obtain a fitting equation and determining the fitting equation as a time-flow relation may be performed as follows:
and performing linear fitting according to the coordinate position to obtain a linear fitting equation, and determining the linear fitting equation as a time flow relation.
The base station calculates the estimated flow value all the time, and in order to guarantee the calculation efficiency, a straight line fitting equation obtained by straight line fitting can be selected to be used as a time flow relational expression.
For example, the straight line fitting may be performed by the least square method to obtain a linear regression equation, i.e., a straight line fitting equation. A fitting equation in which the sum of squares of differences between the estimated first flow values at the historical time and the actual first flow values at the historical time determined from the fitting equation is minimum may be determined as a straight line fitting equation.
For example, a straight line fitting equation is
Wherein x isiIs the time of day or the like,
for a first value of traffic corresponding to time of day, i.e. predicted xiThe first flow value at time, α and β are regression coefficients, i ═ 1,2, …, n, i.e., x1、x2Each of the timings … represents a different time, and n is the number of history times included in the history traffic information. The regression coefficients α and β can be determined according to the least squares method, as follows:
wherein, yiIs xiThe first value of the traffic actually used at the moment, i.e. the historical moment xiThe corresponding first flow value, using the differential method, can be given as follows:
then solving to obtain regression coefficients alpha and beta, and substituting the regression coefficients alpha and beta into
In addition, a time-flow relation can be obtained.
In an embodiment, the operation of determining the first flow value corresponding to the current time according to the time-flow relation and determining the estimated flow value corresponding to the current time according to the first flow value corresponding to the current time may be implemented as follows:
determining a first flow value corresponding to the current moment according to the moment flow relation; determining a first flow value corresponding to a previous moment, and determining an estimated flow value corresponding to the current moment according to the first flow value corresponding to the current moment and the first flow value corresponding to the previous moment.
The estimated first flow value at the current time is obtained by estimating according to the time-flow relational expression, and when the first flow value at the current time may be distorted, that is, the difference between the first flow value at the current time and the first flow value at the previous time is too large, the first flow value corresponding to the previous time can be obtained, and the estimated first flow value at the current time is smoothed according to the first flow value corresponding to the previous time, so that the estimated flow value at the current time is obtained.
The first flow value corresponding to the previous time, that is, the estimated first flow value corresponding to the previous time, may be determined according to the time flow relation, or the first flow value corresponding to the previous time, that is, the first flow value actually used at the previous time, may be determined according to the historical flow information.
In an embodiment, the operation of determining the estimated flow value corresponding to the current time according to the first flow value corresponding to the current time and the first flow value corresponding to the previous time may be implemented by:
multiplying a first traffic value corresponding to the current moment by a first weight to obtain first data, and multiplying a first traffic value corresponding to the previous moment by a second weight to obtain second data; and adding the first data and the second data to obtain an estimated flow value at the current moment.
The first flow value corresponding to the previous time and the estimated first flow value at the current time are multiplied by the corresponding weights respectively and then added, so that the estimated flow value is not distorted with the first flow value at the previous time, and certain smoothness is kept with the first flow value at the previous time. The first weight and the second weight may be preset values, and the sum of the first weight and the second weight may be 1, for example, the weight of the first traffic value at the previous time is 0.5, and the weight of the first traffic value at the current time is 0.5.
Referring to fig. 3, fig. 3 is a schematic block diagram of a structure of an electronic device according to an embodiment of the present application, where the electronic device may be a base station. Referring to fig. 3, the electronic device 100 includes a processor 110 and a memory 120 connected by a system bus, wherein the memory 120 may include a nonvolatile storage medium and an internal memory.
The non-volatile storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause a processor to perform any of the flow pattern determination methods.
The processor is used for providing calculation and control capability and supporting the operation of the whole electronic equipment.
The internal memory provides an environment for the execution of a computer program on a non-volatile storage medium, which when executed by a processor, causes the processor to perform any of the traffic pattern determination methods.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is a block diagram of only a portion of the architecture associated with the subject application, and does not constitute a limitation on the electronic devices to which the subject application may be applied, and that a particular electronic device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
It should be understood that the Processor may be a Central Processing Unit (CPU), and the Processor may be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein, in one embodiment, the processor is configured to execute a computer program stored in the memory to implement the steps of:
determining a pre-estimated flow value corresponding to the current moment according to historical flow information;
respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment;
and determining a target flow mode corresponding to the current moment from the flow mode set according to the pre-estimated flow value and a preset flow value corresponding to each flow mode in the flow mode set.
In an embodiment, when the processor determines the pre-estimated traffic value corresponding to the current time according to the historical traffic information, the processor is configured to:
determining a time flow relation according to historical flow information, wherein the time flow relation is a relation between each time and a first flow value corresponding to each time;
and determining a first flow value corresponding to the current moment according to the moment flow relation, and determining an estimated flow value corresponding to the current moment according to the first flow value corresponding to the current moment.
In one embodiment, the processor, when implementing the determining a temporal traffic relation from historical traffic information, is configured to implement:
determining historical moments included in the historical traffic information and a first traffic value corresponding to each historical moment;
determining the historical time and the corresponding coordinate position of the first traffic numerical value corresponding to each historical time in a preset coordinate system;
and fitting according to the coordinate position to obtain a fitting equation, and determining the fitting equation as a time flow relational expression.
In an embodiment, when the processor determines the first flow value corresponding to the current time according to the time flow relation and determines the estimated flow value corresponding to the current time according to the first flow value corresponding to the current time, the processor is configured to:
determining a first flow value corresponding to the current moment according to the moment flow relation;
determining a first flow value corresponding to a previous moment, and determining an estimated flow value corresponding to the current moment according to the first flow value corresponding to the current moment and the first flow value corresponding to the previous moment.
In an embodiment, when the processor determines the estimated flow value corresponding to the current time according to the first flow value corresponding to the current time and the first flow value corresponding to the previous time, the processor is configured to:
multiplying a first traffic value corresponding to the current moment by a first weight to obtain first data, and multiplying a first traffic value corresponding to the previous moment by a second weight to obtain second data;
and adding the first data and the second data to obtain an estimated flow value at the current moment.
In one embodiment, the traffic pattern set includes a proportional guarantee scheduling pattern and a rate guarantee scheduling pattern, and the processor is configured to, when implementing the respectively determined preset traffic value corresponding to each traffic pattern included in the traffic pattern set, implement:
determining a total first flow value corresponding to the current moment, and determining the product of a preset proportion and the total first flow value as a preset flow value of a proportion guarantee scheduling mode;
and determining the preset flow value of the rate guarantee scheduling mode according to the preset rate flow.
In an embodiment, when the processor determines, according to the pre-estimated flow value and the preset flow value corresponding to each flow mode included in the flow mode set, a target flow mode corresponding to a current time from the flow mode set, the processor is configured to:
and determining a target flow rate mode corresponding to the current moment from the flow rate mode set according to the ratio of the pre-estimated flow rate value to the preset flow rate value corresponding to each flow rate mode in the flow rate mode set.
In an embodiment, when the determining, according to the ratio between the estimated flow value and the preset flow value corresponding to each flow mode included in the flow mode set, a target flow mode corresponding to a current time from the flow mode set is implemented, the processor is configured to implement:
if the estimated flow value is larger than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the largest preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is smaller than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the minimum preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is not greater than the preset flow values corresponding to all the flow modes included in the flow mode set, or the estimated flow value is not less than the preset flow values corresponding to all the flow modes included in the flow mode set, determining the flow mode corresponding to the preset flow value greater than the estimated flow value in the preset flow values corresponding to each flow mode as the target flow mode corresponding to the current moment.
The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, where the computer program includes program instructions, and the processor executes the program instructions to implement any one of the flow pattern determination methods provided in the embodiments of the present application.
The computer-readable storage medium may be an internal storage unit of the electronic device according to the foregoing embodiment, for example, a hard disk or a memory of the electronic device. The computer readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the electronic device.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (11)
1. A method for traffic pattern determination, the method comprising:
determining a pre-estimated flow value corresponding to the current moment according to historical flow information;
respectively determining a preset flow value corresponding to each flow mode in a flow mode set, wherein the preset flow value corresponds to the current moment;
and determining a target flow mode corresponding to the current moment from the flow mode set according to the pre-estimated flow value and a preset flow value corresponding to each flow mode in the flow mode set.
2. The method for determining the flow rate mode according to claim 1, wherein the determining the estimated flow rate value corresponding to the current time according to the historical flow rate information includes:
determining a time flow relation according to historical flow information, wherein the time flow relation is a relation between each time and a first flow value corresponding to each time;
and determining a first flow value corresponding to the current moment according to the moment flow relation, and determining an estimated flow value corresponding to the current moment according to the first flow value corresponding to the current moment.
3. The traffic pattern determination method of claim 2, wherein determining a temporal traffic relationship based on historical traffic information comprises:
determining historical moments included in the historical traffic information and a first traffic value corresponding to each historical moment;
determining the historical time and the corresponding coordinate position of the first traffic numerical value corresponding to each historical time in a preset coordinate system;
and fitting according to the coordinate position to obtain a fitting equation, and determining the fitting equation as a time flow relational expression.
4. The method of claim 3, wherein said fitting from said coordinate locations to obtain a fitted equation and determining said fitted equation as a time-of-day flow relationship comprises:
and performing linear fitting according to the coordinate position to obtain a linear fitting equation, and determining the linear fitting equation as a time flow relation.
5. The method for determining a flow rate mode according to claim 2, wherein the determining a first flow rate value corresponding to a current time according to the time-flow relation and determining an estimated flow rate value corresponding to the current time according to the first flow rate value corresponding to the current time comprises:
determining a first flow value corresponding to the current moment according to the moment flow relation;
determining a first flow value corresponding to a previous moment, and determining an estimated flow value corresponding to the current moment according to the first flow value corresponding to the current moment and the first flow value corresponding to the previous moment.
6. The method for determining a flow rate mode according to claim 5, wherein the determining an estimated flow rate value corresponding to a current time according to the first flow rate value corresponding to the current time and the first flow rate value corresponding to the previous time comprises:
multiplying the first flow value corresponding to the current moment by a first weight to obtain first data, and multiplying the first flow value corresponding to the previous moment by a second weight to obtain second data;
and adding the first data and the second data to obtain an estimated flow value at the current moment.
7. The traffic pattern determination method according to any one of claims 1 to 6, wherein the traffic pattern set includes a proportional guarantee scheduling pattern and a rate guarantee scheduling pattern, and the respectively determining the preset traffic value corresponding to each traffic pattern included in the traffic pattern set includes:
determining a total first flow value corresponding to the current moment, and determining the product of a preset proportion and the total first flow value as a preset flow value of a proportion guarantee scheduling mode;
and determining the preset flow value of the rate guarantee scheduling mode according to the preset rate flow.
8. The method for determining the flow rate mode according to any one of claims 1 to 6, wherein the determining, according to the estimated flow rate value and the preset flow rate value corresponding to each flow rate mode included in the flow rate mode set, the target flow rate mode corresponding to the current time from the flow rate mode set includes:
and determining a target flow rate mode corresponding to the current moment from the flow rate mode set according to the ratio of the pre-estimated flow rate value to the preset flow rate value corresponding to each flow rate mode in the flow rate mode set.
9. The method for determining a flow rate pattern according to claim 8, wherein the determining a target flow rate pattern corresponding to a current time from the flow rate pattern set according to the ratio of the pre-estimated flow rate value to a preset flow rate value corresponding to each flow rate pattern included in the flow rate pattern set comprises:
if the estimated flow value is larger than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the largest preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is smaller than a preset flow value corresponding to each flow mode in the flow mode set, determining a flow mode corresponding to the minimum preset flow value in the preset flow values corresponding to each flow mode as a target flow mode corresponding to the current moment;
if the estimated flow value is not greater than the preset flow values corresponding to all the flow modes included in the flow mode set, or the estimated flow value is not less than the preset flow values corresponding to all the flow modes included in the flow mode set, determining the flow mode corresponding to the preset flow value greater than the estimated flow value in the preset flow values corresponding to each flow mode as the target flow mode corresponding to the current moment.
10. An electronic device, comprising a memory and a processor;
the memory is used for storing a computer program;
the processor for executing the computer program and implementing the flow pattern determination method according to any of claims 1 to 9 when executing the computer program.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the flow pattern determination method according to any one of claims 1 to 9.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010949750.9A CN114258055A (en) | 2020-09-10 | 2020-09-10 | Traffic pattern determination method, electronic device, and storage medium |
| JP2023501837A JP2023534933A (en) | 2020-09-10 | 2021-09-24 | Traffic mode determination method, electronic device and storage medium |
| PCT/CN2021/120363 WO2022053070A1 (en) | 2020-09-10 | 2021-09-24 | Traffic mode determination method, electronic device, and storage medium |
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| CN202010949750.9A CN114258055A (en) | 2020-09-10 | 2020-09-10 | Traffic pattern determination method, electronic device, and storage medium |
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| CN107959640B (en) * | 2016-10-14 | 2020-07-07 | 腾讯科技（深圳）有限公司 | Network service scheduling method and device |
| CN109327866B (en) * | 2018-12-19 | 2022-01-04 | 惠州Tcl移动通信有限公司 | Flow control method, flow control device, mobile terminal and storage medium |
| CN110839040B (en) * | 2019-11-20 | 2021-12-14 | 北京天融信网络安全技术有限公司 | Flow monitoring method, model training method, device and storage medium |
| CN111614634B (en) * | 2020-04-30 | 2024-01-23 | 腾讯科技（深圳）有限公司 | Flow detection method, device, equipment and storage medium |
| CN111626796B (en) * | 2020-07-29 | 2020-12-01 | 北京搜狐新媒体信息技术有限公司 | Flow estimation method and device |
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