CN113852692B - Service determination method, device, equipment and computer storage medium - Google Patents
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Abstract
The embodiment of the application provides a service determination method, a device, equipment and a computer storage medium. The method comprises the following steps: and calculating heat information according to the service information, further calculating heat distribution similarity, and determining the target service according to the heat distribution similarity. According to the service determining method, a more accurate service determining result can be obtained by utilizing the similarity of heat distribution, and user experience is improved.
Description
Technical Field
The present application belongs to the field of mobile communications, and in particular, relates to a service determining method, apparatus, device, and computer storage medium.
Background
At present, the 5G technology supports edge calculation, cloud service is sunk to the network edge through the edge calculation, the cloud service is closer to a user, and better performance can be obtained in aspects of time delay, bandwidth, privacy and the like. However, due to the deployment cost, service scale and other factors, all cloud services cannot be sunk to the user side, and only part of the services can be selected to sink to the edge nodes, and the cooperative service is realized with the cloud or between the edge nodes.
When the prior technical scheme selects partial services needing sinking, the selection is mainly based on the heat, namely, the service with higher heat is deployed to perform collaborative service. An attacker adopts pollution attack aiming at the cooperative service deployment mode based on the heat, maliciously improves the heat of specific services, causes malicious competition, is inaccurate when the sinking service is selected, and seriously influences the service experience of users.
Disclosure of Invention
The embodiment of the application provides a service determining method, device, equipment and computer storage medium, which can determine target service based on heat distribution similarity, obtain more accurate service determining results and improve user experience.
In a first aspect, an embodiment of the present application provides a service determining method, including:
acquiring service information, wherein the service information comprises the number of requests of a plurality of users to a plurality of services in two adjacent service areas;
calculating the heat information of each service based on the service information, wherein the heat information is used for describing the frequency of the service requested by the user;
calculating the distribution similarity of each service heat in two adjacent service areas based on the heat information of each service;
when the similarity of the heat distribution meets the preset condition, determining the service corresponding to the similarity of the heat distribution meeting the preset condition as the target service.
In a second aspect, an embodiment of the present application provides a service determining apparatus, including:
the acquisition module is used for acquiring service information, wherein the service information comprises the number of times of requests of a plurality of users to a plurality of services in two adjacent service areas;
the computing module is used for computing the heat information of each service based on the service information, wherein the heat information is used for describing the frequency of the service requested by the user;
the calculation module is also used for calculating the distribution similarity of the heat of each service in the two adjacent service areas based on the heat information of each service;
and the determining module is used for determining the service corresponding to the heat distribution similarity meeting the preset condition as the target service when the heat distribution similarity meeting the preset condition.
In a third aspect, an embodiment of the present application provides a service determining apparatus, including:
a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the service determination method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the service determination method of the first aspect.
According to the service determining method, device and equipment and the computer storage medium, service heat information can be determined according to the service request times in two adjacent service areas, service heat distribution similarity is calculated, target service is determined based on the service heat distribution similarity, a more accurate service selection result is obtained, and user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.
Fig. 1 is a schematic flow chart of a service determining method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a service determination provided in an embodiment of the present application;
fig. 3 is a system schematic diagram of an application service determining method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a service determining apparatus provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a service determining apparatus provided in an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application are described in detail below to make the objects, technical solutions and advantages of the present application more apparent, and to further describe the present application in conjunction with the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
At present, under a collaboration architecture in edge computing of 5G, collaborative service deployment is realized based on hot statistical information and authoring topology information, but the method is easy to be attacked maliciously, and data pollution is caused. An attacker initiates a request for cold door service through the Internet of things or the intelligent terminal, so that the heat of the cold door service is improved, and the accuracy of service sinking is reduced.
In order to solve the problems in the prior art, embodiments of the present application provide a service determining method, apparatus, device, and computer storage medium. The service determining method provided in the embodiment of the present application will be first described below.
Fig. 1 is a flow chart illustrating a service determining method according to an embodiment of the present application. As shown in fig. 1, the method may include the steps of:
s110, acquiring service information, wherein the service information comprises the number of times of requests of a plurality of users to a plurality of services in two adjacent service areas.
In some embodiments, the service area is defined as a geographic area in which all users can enjoy service under the mobile edge computing (Mobile Edge Computing, MEC) node; the basic service area (Basic Service Area, BSA) is defined as the largest service area of the MEC nodes when not cooperating, and the cooperation service area (Cooperative Service Area, CSA) is defined as one cooperation service area of the basic service area when one MEC node can provide services for users in the basic service area through cooperation.
S120, calculating the heat information of each service based on the service information, wherein the heat information is used for describing the frequency of the service requested by the user.
In some embodiments, the popularity information of each service is calculated according to the number of requests of a plurality of users for a plurality of services in two adjacent service areas, wherein the two adjacent service areas are a basic service area and a collaborative service area.
In one embodiment, the sum of the number of requests of users in two adjacent service areas for each service is calculated as the hotness value for each service. For example, the number of user requests of a service in the basic service area is 40, and the number of user requests in the collaborative service area is 50, the popularity value of the service is 90.
S130, calculating the similarity of the distribution of the heat of each service in two adjacent service areas based on the heat information of each service.
In some embodiments, the service heat distribution similarity Sim is calculated as follows:
wherein p is i，c For the heat value, p, of the service c in the basic service area corresponding to the MEC node i j，c For the popularity value of service c in the collaboration service area corresponding to MEC node j, sim (p i，c ，p j，c ) And (5) distributing similarity for service c in the basic service area and the cooperative service area.
And S140, when the similarity of the heat distribution meets the preset condition, determining the service corresponding to the similarity of the heat distribution meeting the preset condition as the target service.
According to the service determining method provided by the embodiment of the invention, the heat information of the service can be determined according to the request times of the service in two adjacent service areas, the heat distribution similarity of the service in the two service areas is calculated according to the heat information, the similarity can reflect whether the service is the service with abnormally increased request times in a certain service area, and the target service is determined based on the similarity, so that the service determining result is more accurate.
In some embodiments, calculating the similarity of the heat distribution of each service in the two adjacent service areas based on the heat information of each service includes: and when the sum of the request times of each service in the two service areas is not smaller than a first threshold value, calculating the similarity of the distribution of the heat of each service in the two adjacent service areas based on the heat information of each service. By setting the first threshold value, error problems due to smaller data values can be avoided. For example, a service c is requested 1 time in the BSA area and 0 time in the CSA area, and the calculated similarity of the heat distribution of the service is 0, but in reality, the number of requests of the service in the two areas is very close and only 1 time different, and the calculation result is in error. This error is always present when the request count data is small. The specific value of the first threshold may be set according to practical situations, which is not limited.
In some embodiments, when the heat distribution similarity satisfies a preset condition, determining a service corresponding to the heat distribution similarity satisfying the preset condition as the target service includes: clearing service information corresponding to the heat distribution similarity, wherein the heat distribution similarity does not meet the preset condition; and determining the service corresponding to the heat distribution similarity with the heat distribution similarity meeting the preset condition as the target service based on the cleared service information and the heat information. When the similarity of the heat distribution does not meet the preset condition, the corresponding service is judged to be pseudo heat service, namely, the service with abnormally increased user request times is judged to be pseudo heat service, service information of the service is cleared, and target service is determined based on the cleared service information.
In some embodiments, the preset condition is that the heat distribution similarity is greater than a second threshold; when the similarity of the heat distribution meets a preset condition, determining the service corresponding to the similarity of the heat distribution meeting the preset condition as a target service comprises the following steps: and when the similarity of the heat distribution is larger than the second threshold, determining the service corresponding to the similarity of the heat distribution meeting the preset condition as the target service based on the heat information of each service.
In some embodiments, when the similarity of the heat distribution is greater than the second threshold, determining, based on the heat information of each service, a service corresponding to the similarity of the heat distribution that satisfies a preset condition as a target service includes: determining a first service corresponding to the heat distribution similarity which is larger than a second threshold; and determining a preset number of services in the first service as target services according to the user request frequency of the first service. And determining the service with the similarity of the heat distribution larger than the second threshold value as a first service, and selecting a preset number of services as target services according to the user request frequency from large to small in the first service. The preset number may be set, and specific values are not limited.
In some embodiments, when the heat distribution similarity satisfies a preset condition, determining a service corresponding to the heat distribution similarity satisfying the preset condition as the target service includes: when the similarity of the heat distribution meets the preset condition, determining a target service based on the service corresponding to the similarity of the heat distribution meeting the preset condition and a weight value preset by each service. When the similarity of the heat distribution meets the preset condition, combining the service weight and the service heat information, and determining the target service in the service corresponding to the similarity of the heat distribution meeting the preset condition.
In some embodiments, the method further comprises: calculating service heat similarity mean and variance based on each service heat distribution similarity; a target first threshold is calculated based on the service heat mean and variance, the target first threshold being used to update the first threshold. Service heat similarity mean S i，j The calculation formula of (2) is as follows:
service heat similarity varianceThe calculation formula of (2) is as follows:
wherein C' i，j To satisfy a set of services for which the sum of the number of user requests in two service areas is greater than a first threshold, a first threshold is targetedThe calculation formula of (2) is as follows:
wherein, alpha is a coefficient, the recommended value is between 2 and 3, and the specific value is not limited.
In some embodiments, the service determination process is performed periodically, and the period duration may be set, which is not limited thereto.
According to the service determining method provided by the embodiment of the invention, the distribution similarity can be calculated according to the heat information of the service, the service is selected according to the distribution similarity and the heat information, and whether the service belongs to the contaminated service, namely the service with abnormally increased user request times can be judged through the heat distribution similarity, so that more accurate target service can be obtained, and user experience is improved.
In one embodiment, three rounds of data collected for the i service area and the j service area are:
i＝{a：100，b：80，c：60，d：40，e：20a：90，b：100，c：80，d：70，e：50a：80，b：80，c：100，d：70，h：60}
j＝{a:80，b:90，c:70，d:60，e:40a:100，f:100，c:90，d:50，e:80a:90，b:70，c:90，d:80，h:100}
vip= [ a, b ] is set, i.e. weights of a, b are set, and service a and service b are preferentially selected. Wherein a, b, c, d, e, f, h represent different services. From the data, the data of the third round of data of the i service area shows the data of the abnormal growth of the service h, the data of the abnormal growth of the service f shows the data of the second round of data of the j service area, and the data of the abnormal growth of the service h shows the data of the third round of data.
Setting the preset number of target services as 3, and obtaining the following calculation result according to the data:
hotspot services [ a:180, b:170, c:130, d:100]
Target services [ a, b, c ]
Hotspot services [ a:190, c:170, e:140]
Target services [ a, c, e ]
Hotspot services [ c:190, a:170, j:160, b:150, d:150]
Target service [ c, a, b ]
In one embodiment, as shown in fig. 2, the service determining method includes traversing the services in the j service areas, calculating the number of requests in the two service areas for the service c with the two service areas, and calculating the similarity of heat distribution of the service c in the two service areas when the number of requests is greater than a first threshold. After traversing all services in the j service areas, forming an intersection by the services with the request times larger than a first threshold value in the two service areas, calculating the mean value and variance of the similarity of the heat distribution of all the services, and updating the first threshold value in the next service determination flow according to the mean value and variance. And cleaning the service information on-line heat pollution information according to the calculated heat distribution similarity, namely cleaning the service information which does not meet the condition that the heat distribution similarity is larger than a second threshold value. Traversing the two service areas according to the cleaned service information, traversing j service area services, constructing a service intersection meeting the requirement that the sum of the request times in the two service areas is larger than a first threshold value, traversing the intersection service, calculating the similarity of the heat distribution of the service in the intersection in the two service areas, and correcting the request times of the service in the two service areas when the similarity of the heat distribution is not larger than a second threshold value. After traversing the intersection services, correcting the intersection services meeting the preset conditions, updating a first threshold value, a heat distribution similarity mean value and a variance, sorting based on weight and heat information, selecting a preset number of services as target services, and caching the target services in a service area.
Fig. 3 is a system schematic diagram of an application service determining method, where the system includes: the system comprises a data recording unit, a heat statistics and strategy sharing unit and a heat cleaning unit.
The data recording unit is used for recording service request information of the user;
a heat cleaning unit for executing the service determining method;
and the heat statistics and policy sharing unit is used for counting service heat information under the MEC nodes and updating and sharing based on the determined service.
Based on the above service determining method, the embodiment of the application also provides a service determining device, which specifically comprises the following steps:
fig. 4 is a schematic structural diagram of a device according to an embodiment of the present application. As shown in fig. 4, the apparatus 400 may include an acquisition module 410, a calculation module 420, and a determination module 430.
An obtaining module 410, configured to obtain service information, where the service information includes the number of requests of multiple users for multiple services in two adjacent service areas;
a calculation module 420, configured to calculate, based on the service information, heat information of each service, where the heat information is used to describe a frequency of service requested by a user;
the calculating module 420 is further configured to calculate a similarity of heat distribution of each service in the two adjacent service areas based on the heat information of each service;
the determining module 430 is configured to determine, when the similarity of the heat distribution satisfies a preset condition, that a service corresponding to the similarity of the heat distribution that satisfies the preset condition is a target service.
The service determining device provided by the embodiment of the invention can calculate the heat information of the service according to the service information, further calculate the heat distribution similarity of the service in the two service areas, determine the target service based on the heat distribution similarity, obtain a more accurate determination result and improve the user experience.
In some embodiments, the calculating module 420 is configured to calculate, based on the heat information of each service, a similarity of heat distribution of each service in two adjacent service areas, including: and when the sum of the number of user requests of each service in the two service areas is not smaller than a first threshold value, calculating the similarity of the distribution of the heat of each service in the two adjacent service areas based on the heat information of each service.
In some embodiments, the determining module 430 is configured to determine, when the similarity of the heat distribution meets a preset condition, a service corresponding to the similarity of the heat distribution that meets the preset condition as a target service, including: clearing service information corresponding to the heat distribution similarity, wherein the heat distribution similarity does not meet the preset condition; and determining the service corresponding to the heat distribution similarity with the heat distribution similarity meeting the preset condition as the target service based on the cleared service information and the heat information.
In some embodiments, the preset condition is that the heat distribution similarity is greater than a second threshold; the determining module 430 is configured to determine, when the similarity of the heat distribution meets a preset condition, a service corresponding to the similarity of the heat distribution that meets the preset condition as a target service, where the determining module includes: and when the similarity of the heat distribution is larger than a second threshold value, determining the service corresponding to the similarity of the heat distribution meeting the preset condition as the target service based on the heat information of each service.
In some embodiments, the determining module 430 is configured to determine, based on the heat information of each service, that the service corresponding to the heat distribution similarity satisfying the preset condition is a target service when the heat distribution similarity is greater than the second threshold, including: determining a first service corresponding to the heat distribution similarity larger than a second threshold; and determining a preset number of services in the first service as target services according to the user request frequency of the first service.
In some embodiments, the determining module 430 is configured to determine, when the similarity of the heat distribution meets a preset condition, a service corresponding to the similarity of the heat distribution that meets the preset condition as a target service, including: when the similarity of the heat distribution meets the preset condition, determining a target service based on the service corresponding to the similarity of the heat distribution meeting the preset condition and a weight value preset by each service.
In some embodiments, the calculation module 420 is further configured to calculate a service heat similarity mean and variance based on each service heat distribution similarity; a target first threshold is calculated based on the service heat mean and variance, the target first threshold being used to update the first threshold.
The service determining device provided by the embodiment of the invention can calculate the heat information of the service according to the service information, further calculate the heat distribution similarity of the service in the two service areas, and determine the target service based on the heat distribution similarity, wherein the heat distribution similarity can reflect whether the service has abnormal increase of the number of user requests in a certain service area, avoid selecting the problem service, and obtain a more accurate service determining result.
Fig. 5 shows a schematic hardware structure of service determination provided in an embodiment of the present application.
The service determining device may comprise a processor 501 and a memory 502 storing computer program instructions.
In particular, the processor 501 may include a central processing unit (Central Processing Unit, CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of embodiments of the present application.
Memory 502 may include mass storage for data or instructions. By way of example, and not limitation, memory 502 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. In one example, memory 502 may include removable or non-removable (or fixed) media, or memory 502 may be a non-volatile solid state memory. Memory 502 may be internal or external to the integrated gateway disaster recovery device.
In one example, memory 502 may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, memory 502 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to a method according to an aspect of the present application.
The processor 501 reads and executes the computer program instructions stored in the memory 502 to implement the methods/steps S100 to S140 in the embodiment shown in fig. 1, and achieve the corresponding technical effects achieved by executing the methods/steps in the embodiment shown in fig. 1, which are not described herein for brevity.
In one example, the service determination device may also include a communication interface 503 and a bus 510. As shown in fig. 5, the processor 501, the memory 502, and the communication interface 503 are connected to each other by a bus 510 and perform communication with each other.
The communication interface 503 is mainly used to implement communication between each module, apparatus, unit and/or device in the embodiments of the present application.
Bus 510 includes hardware, software, or both that couple the components of the service determination device to one another. By way of example, and not limitation, the buses may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) Bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (Industry Standard Architecture, ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a micro channel architecture (MCa) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus, or a combination of two or more of the above. Bus 510 may include one or more buses, where appropriate. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.
The service determining device may calculate the heat information and the service heat distribution information based on the acquired service information, so as to execute the service determining method in the embodiment of the present application, thereby implementing the service determining method described in connection with fig. 1.
In addition, in combination with the service determining method in the above embodiment, the embodiment of the application may be implemented by providing a computer storage medium. The computer storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the service determination methods of the above embodiments.
It should be clear that the present application is not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be different from the order in the embodiments, or several steps may be performed simultaneously.
Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that 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, which are intended to be included in the scope of the present application.
Claims (8)
1. A method of service determination, the method comprising:
acquiring service information, wherein the service information comprises the number of times of requests of a plurality of users for a plurality of services in two adjacent service areas, the service areas are geographic areas, and all users in the geographic areas can enjoy the services under a mobile edge computing node;
calculating heat information of each service based on the service information, wherein the heat information is used for describing the frequency of the service requested by a user;
when the sum of the number of user requests of each service in the two service areas is not smaller than a first threshold value, calculating the similarity of each service heat distribution in the two adjacent service areas based on the heat information of each service;
when the heat distribution similarity meets a preset condition, determining that a service corresponding to the heat distribution similarity meeting the preset condition is a target service, wherein the target service is a service for calculating from a cloud service to an edge network;
wherein the preset condition is that the similarity of the heat distribution is larger than a second threshold; when the heat distribution similarity meets a preset condition, determining that the service corresponding to the heat distribution similarity meeting the preset condition is a target service comprises the following steps:
when the heat distribution similarity is larger than the second threshold, determining that the service corresponding to the heat distribution similarity meeting the preset condition is a target service based on the heat information of each service;
the calculation formula of the service heat distribution similarity is as follows:
wherein p is i,c For the heat value, p, of the service c in the basic service area corresponding to the MEC node i j,c For the popularity value of service c in the collaboration service area corresponding to MEC node j, sim (p i,c ,p j,c ) And (5) distributing similarity for service c in the basic service area and the cooperative service area.
2. The method according to claim 1, wherein when the heat distribution similarity satisfies a preset condition, determining that a service corresponding to the heat distribution similarity satisfying the preset condition is a target service includes:
clearing service information corresponding to the heat distribution similarity, wherein the heat distribution similarity does not meet a preset condition;
and determining the service corresponding to the heat distribution similarity, which satisfies the preset condition, as the target service based on the cleared service information and the heat information.
3. The method according to claim 1, wherein when the heat distribution similarity is greater than the second threshold, determining, based on the heat information of each service, a service corresponding to the heat distribution similarity satisfying a preset condition as a target service includes:
determining a first service corresponding to the heat distribution similarity greater than the second threshold;
and determining a preset number of services in the first service as target services according to the user request frequency of the first service.
4. The method according to claim 1, wherein when the heat distribution similarity satisfies a preset condition, determining that a service corresponding to the heat distribution similarity satisfying the preset condition is a target service includes:
and when the heat distribution similarity meets a preset condition, determining a target service based on the service corresponding to the heat distribution similarity meeting the preset condition and a weight value preset by each service.
5. The method according to claim 1, wherein the method further comprises:
calculating service heat similarity mean and variance based on the service heat distribution similarity;
calculating a target first threshold value based on the service heat mean value and the variance, wherein the target first threshold value is used for updating a first threshold value in the next service determination flow;
the calculation formula of the service heat similarity mean value is as follows:
the calculation formula of the service heat similarity variance is as follows:
C i ′ ,j to satisfy a service aggregate set in which a sum of the number of user requests in two service areas is greater than a first threshold;
the calculation formula of the target first threshold is as follows:
where α is a constant.
6. A service determining apparatus, the apparatus comprising:
the system comprises an acquisition module, a service information acquisition module and a service information processing module, wherein the acquisition module is used for acquiring service information, the service information comprises the number of times of requests of a plurality of users for a plurality of services in two adjacent service areas, the service areas are geographic areas, and all the users in the geographic areas can enjoy the services under a mobile edge computing node;
a calculation module, configured to calculate, based on the service information, heat information of each service, where the heat information is used to describe a frequency of the service requested by a user;
the calculation module is further configured to calculate, when the sum of the number of user requests of each service in the two service areas is not less than a first threshold, a similarity of each service heat distribution in two adjacent service areas based on the heat information of each service;
the determining module is used for determining that the service corresponding to the heat distribution similarity meeting the preset condition is a target service when the heat distribution similarity meeting the preset condition is met, wherein the target service is a service for calculating from a cloud service to an edge network;
wherein the preset condition is that the similarity of the heat distribution is larger than a second threshold; the determining module is specifically configured to:
when the heat distribution similarity is larger than the second threshold, determining that the service corresponding to the heat distribution similarity meeting the preset condition is a target service based on the heat information of each service;
the calculation formula of the service heat distribution similarity is as follows:
wherein p is i,c For the heat value, p, of the service c in the basic service area corresponding to the MEC node i j,c For the popularity value of service c in the collaboration service area corresponding to MEC node j, sim (p i,c ,p j,c ) And (5) distributing similarity for service c in the basic service area and the cooperative service area.
7. A service determining apparatus, the apparatus comprising: a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the service determination method according to any of claims 1-5.
8. A computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the service determination method of any of claims 1-5.
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