Method for determining target server in mobile Internet of Vehicles and target request equipment

Abstract

The invention relates to the technical field of mobile edge computing, and discloses a method for determining a target server in a mobile internet of vehicles, the method is applied to a target request device, and the method comprises the following steps: obtaining a matching score between a requester class group and a service device; wherein the service equipment is mobile equipment capable of providing services; determining the matching score meeting a first preset condition as a target matching score; sending a service request to service equipment corresponding to the target matching score, and triggering the service equipment to send feedback information to target request equipment; and receiving feedback information sent by the service equipment, and determining the service equipment with the sent feedback information as acceptance information and meeting a second preset condition as a target server of all request equipment in the requester class group. According to the method, the working pressure of the edge server can be reduced. The invention further discloses target request equipment, service equipment and electronic equipment.

Description

Technical Field

[0001] The present application relates to the field of mobile edge computing technology, for example, to a method for determining a target server in a mobile vehicle network, a target request device, a service device, and an electronic device. Background Art

[0002] Mobile edge computing technology is a technology that deploys edge servers near mobile terminal devices and moves computing tasks and data storage to edge servers for processing. For example, by offloading the computing tasks of mobile devices to edge servers through task offloading technology, the computing tasks with large computing tasks and short latency requirements can be met. This solves the problem of insufficient computing resources for mobile devices. It also reduces the cache pressure of mobile devices by caching the content on mobile devices to edge servers. In mobile vehicle networking, with the increase in the number of cars, the intelligence of cars is also constantly improving, such as autonomous driving, image-assisted navigation, autonomous driving, etc., which makes the computing tasks and cache content of vehicles grow rapidly, and also brings a large burden to edge servers. Therefore, how to reduce the working pressure of edge servers has become an urgent problem to be solved.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0004] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0005] The embodiments of the present disclosure provide a method for determining a target server, a target request device, a service device, and an electronic device, so as to reduce the working pressure of an edge server.

[0006] In some embodiments, a method for determining a target server in a mobile vehicle network is applied to a target requesting device, wherein the target requesting device is a requesting device in a requesting party group, wherein the requesting party group includes at least one requesting device, and the requesting device is a mobile device that needs to be served. The method comprises: obtaining a matching score between the requesting party group and a service device; wherein the service device is a mobile device that can provide services; determining a matching score that satisfies a first preset condition as a target matching score; sending a service request to a service device corresponding to the target matching score, triggering the service device to send feedback information to the target requesting device; receiving feedback information sent by the service device, and treating the sent feedback information as acceptance information, and determining the service device that satisfies a second preset condition as the target server for all requesting devices in the requesting party group.

[0007] In some embodiments, a method for determining a target server in a mobile vehicle network is applied to a service device, wherein the service device is a mobile device capable of providing services, and the method comprises: upon receiving a service request sent by a target requesting device, obtaining a matching index between the requesting party group to which the target requesting device belongs and the service device; wherein the requesting party group includes at least one requesting device, the target requesting device is a requesting device in the requesting party group, and the requesting device is a mobile device that needs to be provided with services; based on the matching index, feedback information is sent to the target requesting device, and the target requesting device is triggered to set the feedback information as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesting devices in the requesting party group.

[0008] In some embodiments, a method for determining a target server in a mobile vehicle network is applied to an electronic device, the method comprising: obtaining device power, device capabilities, and service provision prices of at least two mobile devices; using a third preset algorithm to calculate the device power, device capabilities, and service provision prices of each mobile device, respectively, to obtain an identity evaluation score for each mobile device; determining the identity information of the corresponding mobile device based on the identity evaluation score of each mobile device; in a case where the identity information is a service device, sending the service device identity information to the corresponding mobile device, triggering the service device to receive a service request sent by a target request device, and obtaining a matching indicator between the requester group to which the target request device belongs and the service device. number, and according to the matching index, send feedback information to the target request device; in the case where the identity information is a request device, perform a clustering operation on each request device to obtain at least one request party group; select a request device from each request party group according to the preset rule, and determine the identity information of the selected request device as the target request device; send the target request device identity information to the corresponding request device, trigger the target request device to obtain the matching score between the corresponding request party group and the service device, and trigger the target request device to receive the feedback information sent by the service device, and determine the sent feedback information as acceptance information, and the service device that meets the second preset condition is determined as the target server for all request devices in the request party group.

[0009] In some embodiments, the target request device includes: a first processor and a first memory storing first program instructions, and the first processor is configured to execute the above-mentioned method for determining the target server when running the first program instructions.

[0010] In some embodiments, the service device includes: a second processor and a second memory storing second program instructions, and the second processor is configured to execute the above-mentioned method for determining the target server when running the second program instructions.

[0011] In some embodiments, the electronic device includes: a third processor and a third memory storing third program instructions, and the third processor is configured to execute the above-mentioned method for determining the target server when running the third program instructions.

[0012] The method, target request device, service device and electronic device for determining the target server in the mobile vehicle network provided by the embodiments of the present disclosure can achieve the following technical effects: the target request device obtains the matching score between the requesting party group and each service device, and sends a service request to the service device corresponding to the matching score that satisfies the first preset condition. When the feedback information received from the service device is an acceptance message, and the service device also satisfies the second preset condition, the service device is determined as the target server for all requesting devices in the requesting party group. In this way, the service device is used as the target server for the requesting device. It can facilitate the requesting device to offload the computing task or cache the content to the target server, so that the target server can process the computing task or content cache for the requesting device. Therefore, there is no need for the requesting device to offload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server.

[0013] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein: Figure 1 is a schematic diagram of a method for determining a target server provided by an embodiment of the present disclosure; Figure 2 is a schematic diagram of another method for determining a target server provided by an embodiment of the present disclosure; Figure 3 is a schematic diagram of another method for determining a target server provided by an embodiment of the present disclosure; Figure 4 is a schematic diagram of another method for determining a target server provided by an embodiment of the present disclosure; Figure 5 is a schematic diagram of another method for determining a target server provided by an embodiment of the present disclosure; Figure 6 is a structural diagram of a target request device provided by an embodiment of the present disclosure; Figure 7 is a structural diagram of a service device provided by an embodiment of the present disclosure; Figure 8 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0015] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0016] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0017] Unless otherwise stated, the term "plurality" means two or more.

[0018] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0019] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0020] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0021] Mobile devices include smart phones, tablet computers, smart watches or vehicles. In mobile car networking, vehicles are used as mobile devices. With the rapid growth of the number of vehicles and the amount of computing tasks, if the computing tasks of mobile vehicles are all unloaded to edge servers, or mobile vehicles cache content to edge servers, it will bring a large burden to the edge servers. The method for determining the target server provided by the embodiment of the present disclosure can match the target server for the computing tasks or content caching tasks of mobile vehicles in the car networking, thereby reducing the working pressure of the edge server. In the embodiment of the present disclosure, the electronic device obtains the device power, device capabilities and service prices of multiple mobile devices, and divides the multiple mobile devices into two categories of requesting devices and service devices according to the device power, device capabilities and service prices of each mobile device. Among them, the electronic device includes a computer, a server or a base station. The requesting device is a mobile device that needs to be provided with services, that is, the requesting device is a mobile device that needs to unload computing tasks or cache content to a server. The service device is a mobile device that can provide services. That is, the service device is a mobile device that can provide task computing or content caching for the requesting device. At the same time, the electronic device clusters the requesting devices to obtain at least one requesting party group. In this way, the requesting party group contains at least one requesting device. In addition, the electronic device selects a requesting device from each requesting party group as the target requesting device of the requesting party group according to the preset rules. The target requesting device is matched with each service device to determine the service device that matches the target requesting device, and the matched service device is determined as the target server for all requesting devices in the requesting party group where the corresponding target requesting device is located. In this way, the service device is used as the target server of the requesting device. It is convenient for the requesting device to unload the computing task or cache the content to the target server, so that the service device can process the computing task or content cache for the requesting device. Therefore, the requesting device does not need to unload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server. In addition, the target requesting device is matched with each service device as a representative of the requesting party group, and all requesting devices do not need to match with each service device, which can reduce the amount of calculation and improve the operation rate.

[0022] Combination Figure 1 As shown, the embodiment of the present disclosure provides a method for determining a target server in a mobile vehicle network, the method is applied to a target requesting device, the target requesting device is a requesting device in a requesting party group, the requesting party group includes at least one requesting device, and the requesting device is a mobile device that needs to be provided with a service. That is, the requesting device is a mobile device that needs to be provided with a task computing service or a content caching service. The mobile device is a vehicle. The method includes: Step S101, obtaining a matching score between a requester group and a service device. A service device is a mobile device that can provide services. That is, a service device is a mobile device that can provide task computing services or content caching services for a requester. The requester group is the requester group to which the target requester belongs.

[0023] Step S102: determining a matching score that meets a first preset condition as a target matching score.

[0024] Step S103: sending a service request to a service device corresponding to the target matching score, triggering the service device to send feedback information to the target requesting device.

[0025] Step S104: receiving feedback information sent by the service device, and determining the service device whose sent feedback information is acceptance information and meets the second preset condition as the target server of all requesting devices in the requesting party group.

[0026] According to the method for determining the target server in the mobile vehicle network provided by the embodiment of the present disclosure, the target requesting device obtains the matching score between the requesting party group and each service device, and sends a service request to the service device corresponding to the matching score that satisfies the first preset condition. When the feedback information sent by the service device is an acceptance message, and the service device satisfies the second preset condition at the same time, the service device is determined as the target server for all requesting devices in the requesting party group. In this way, the service device is matched with the requesting device to realize the service device as the target server of the requesting device. It is convenient for the requesting device to offload the computing task or cache the content to the target server, so that the service device can process the computing task or content cache for the requesting device. Therefore, there is no need for the requesting device to offload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server. At the same time, the service device provides computing tasks or content caches for the requesting device, and the distance between the devices is short, which can also reduce the communication cost.

[0027] Furthermore, the target requesting device is matched with each service device as a representative of the requesting party group, so that all requesting devices in the requesting party group do not need to be matched with each service device, which can reduce the amount of calculation and improve the operation rate.

[0028] Furthermore, obtaining the matching score between the requester group and the service device includes: obtaining a first average value, a second average value, and a third average value. The first average value is the average value of the matching values ​​between the moving trajectories of the requester devices originating from mobile vehicles in the requester group and the moving trajectories of the service device. The second average value is the average value of the matching values ​​between the task types of the requester devices in the requester group and the task types of the service device. The third average value is the average value of the matching values ​​between the service prices borne by the requester devices in the requester group and the service prices provided by the service device. The first preset algorithm is used to calculate the first average value, the second average value, and the third average value to obtain the matching score between the requester group and the service device.

[0029] The higher the matching score between the requester group and the service device, the more the requester group matches the corresponding service device. In addition, when the target requester obtains the matching situation between the requester group and the service device, the matching situation of the movement trajectory, the matching situation of the task type, and the matching situation of the price to be borne and the service price between each requester device from the mobile vehicle in the requester group and the service device are considered. The matching situation between the requester group and each service device can be obtained more accurately. This makes the confirmed target server more in line with the requirements of each requester device in the requester group.

[0030] Optionally, using a first preset algorithm to calculate the first average value, the second average value, and the third average value to obtain a matching score between the requester group and the service device includes: calculating Obtain the matching score between the requester group and the service device. For the m The requester group and n The matching score of each service device. For the m The movement trajectories of the requesting devices from the mobile vehicles in the requesting party groups are respectively n The average value of the matching values ​​between the movement trajectories of the service devices. For the m The task type of each requesting device in the requester group is respectively n The average value of the matching value between the task types of the service devices. For the m The service price borne by each requesting device in the requesting party group is n The average value of the matching value between the service prices provided by the service devices. is the first trajectory impact factor, is the task type influencing factor, is the price influencing factor, , , , + + =1.

[0031] Furthermore, obtaining a first average value includes: obtaining a matching value between a movement trajectory of each requesting device in the requesting party group and a movement trajectory of the service device, and calculating the matching value between a movement trajectory of each requesting device in the requesting party group and a movement trajectory of the service device to obtain a first average value.

[0032] By calculation Get the m The movement trajectory of each requesting device in the requesting party group is respectively n The average value of the matching value between the moving trajectories of the service devices. For the m The requester group i The movement trajectory of the requesting device is n The matching value between the movement trajectories of the service devices. k Indicates m The number of all requesting devices in the requester group.

[0033] Furthermore, obtaining the matching value between the movement trajectory of each requesting device in the requesting party group and the movement trajectory of the service device includes: obtaining the historical position coordinates of each requesting device in the requesting party group and the predicted position coordinates at the next moment, and obtaining the historical position coordinates of the service device and the predicted position coordinates at the next moment. The historical position coordinates of each requesting device in the requesting party group and the predicted position coordinates at the next moment, as well as the historical position coordinates of the service device and the predicted position coordinates at the next moment are calculated to obtain the matching value between the movement trajectory of each requesting device in the requesting party group and the movement trajectory of the service device.

[0034] By calculation Get the m of the requester groups i The movement trajectory of the requesting device is n The matching value between the moving trajectories of the service devices. For the i The number of coordinate points of the moving trajectory of the requesting device is the same as that of the serving device. The moving trajectory coordinate points are longitude and latitude coordinate points. For the m of the requester groups i Requesting devices in The historical position coordinates at the time, For then Service equipment in The historical position coordinates at the time, ( ) indicates the calculation of m of the requester groups i The requesting device and n Service equipment in The distance between the historical position coordinates at the time, For the n The predicted location coordinates of the service device at the next moment, For the m of the requester groups i The predicted location coordinates of the requesting device at the next moment, Indicates the calculation m of the requester groups i The requesting device and n The distance between the predicted location coordinates of the service devices at the next moment. The predicted location coordinates are longitude and latitude coordinates.

[0035] Further, n The predicted location coordinates of the service device at the next moment are obtained by the following method: n The historical movement trajectory of the service equipment. n The historical movement trajectory of each service device is input into the preset neural network to obtain the n The estimated location coordinates of the service device at the next moment. n The estimated position coordinates of the service device at the next moment are corrected to obtain the n The predicted location coordinates of a service device at the next moment. The preset neural network is a neural network based on LSTM-Attention. The estimated location coordinates are longitude and latitude coordinates.

[0036] Furthermore, for n The estimated position coordinates of the service device at the next moment are corrected, including: n The estimated location coordinates of the service device at the next moment are taken as the center, and all roads within the preset radius are determined as the first candidate roads, and the road data of the first candidate roads are obtained. The road data includes: the coordinates of all points on the road, the roads connected to the road, the road type and the road direction. n The corresponding scores between the estimated position coordinates of the service device at the next moment and each first candidate road. The first candidate road corresponding to the maximum corresponding score is determined as the first target road. The coordinates of the point on the first target road closest to the first estimated position coordinates are determined as the first target road. nThe predicted location coordinates of the service device at the next moment. The first estimated location coordinates are n The estimated location coordinates of a service device at the next moment. The predicted location coordinates are longitude and latitude coordinates.

[0037] By first inputting the historical movement trajectory of the service equipment into the neural network to estimate the location coordinates at the next moment, and then correcting the estimated location coordinates based on the road data of the road where the estimated location coordinates are located and the surrounding roads, the predicted location coordinates of the service equipment at the next moment can be predicted more accurately.

[0038] Further, according to the road data of each first candidate road, the first n The corresponding scores between the estimated position coordinates of each service device at the next moment and each first candidate road include: By calculation Get the n The estimated location coordinates of the service device at the next moment are j The corresponding scores between the first alternative roads. For the n The estimated location coordinates of the service device at the next moment are j The corresponding scores between the first alternative roads. The normalized coordinates of the first estimated position to the j The shortest distance of the first alternative road. For the j The connection status of the first candidate road and the road where the first estimated position coordinates are located. For the n The historical moving trajectory direction of the service device j The angle fraction of the road direction of the first alternative road. For the j The road grade score of the first alternative road. is the first distance influencing factor, is the first connection condition influencing factor, is the first angle influencing factor, is the first road grade score influencing factor, , , , , .

[0039] Furthermore, by calculating Get the j The connection between the first candidate road and the road where the first estimated position coordinates are located. For the j The first alternative road and then The shortest number of transit roads required to connect the roads where the service equipment is located, for example, j The first alternative road and the n The roads where the service equipment are located are directly connected. ; If j The first alternative road and the n If there is one road between the roads where the service equipment is located, ; If j The first alternative road and the n If there are two roads between the roads where the service equipment is located, ; and so on. That is, if the j The first alternative road and the n The distance between the roads where the service equipment is located s road, then .

[0040] Furthermore, by calculating Get the n The historical moving trajectory direction of the service device j The angle fraction of the road direction of the first candidate road. . For the n The moving angle of the service device’s recent historical moving trajectory, For the n Service equipment in t The geographical location coordinates at the time, For the n Service equipment in t -1 The geographic location coordinates at the moment, which are the longitude and latitude coordinates, For the j The road direction angle of the first alternative road.

[0041] Further, the following method is used to obtain j The road grade score of the first alternative road: Get the road grade score of the first alternative road j The road type of the first alternative road, using the j The road type of the first candidate road is searched in the preset data table to find the j The road grade score corresponding to the road type of the first candidate road. The corresponding relationship between the road type and the road grade score is stored in the preset data table.

[0042] In some embodiments, a preset data table stores a road grade score of 1 for a highway type, a road grade score of 0.9 for a trunk road type, a road grade score of 0.8 for a first-class highway type, a road grade score of 0.7 for a second-class highway type, a road grade score of 0.6 for a third-class highway type, a road grade score of 0.5 for an unclassified road type, a road grade score of 2 for a living street type, a road grade score of 0.2 for a residential road type, a road grade score of 0.2 for an emergency escape passage type, a road grade score of 0.4 for an ordinary road type, a road grade score of 0.1 for a pedestrian street type, a road grade score of 0.1 for a small path type, and so on.

[0043] Further, m of the requester groups i The predicted position coordinates of the requesting device at the next moment are obtained by: m of the requester groups i The historical movement trajectory of the requested device. m of the requester groups i The historical movement trajectory of the requesting device is input into the preset neural network to obtain the second estimated position coordinates. The second estimated position coordinates are m of the requester groups i The estimated position coordinates of the requesting device at the next moment. Correct the second estimated position coordinates to obtain the m of the requester groups i The predicted location coordinates of the requesting device at the next moment.

[0044] Further, the second estimated position coordinates are corrected, including: determining all roads within a preset radius with the second estimated position coordinates as the second candidate roads, and obtaining road data of the second candidate roads. According to the road data of each second candidate road, obtaining the corresponding score between the second estimated position coordinates and each second candidate road. Determining the second candidate road corresponding to the maximum corresponding score as the second target road. Determining the coordinates of the point on the second target road closest to the second estimated position coordinates as the second target road. m of the requester groups i The predicted location coordinates of the requesting device at the next moment. The predicted location coordinates are longitude and latitude coordinates.

[0045] By first inputting the historical movement trajectory of the requesting device into the neural network to estimate the position coordinates at the next moment, and then correcting the estimated position coordinates based on the road data of the road where the estimated position coordinates are located and the surrounding roads, the predicted position coordinates of the requesting device at the next moment can be predicted more accurately.

[0046] Furthermore, according to the road data of each second candidate road, obtaining the corresponding score between the second estimated position coordinate and each second candidate road includes: calculate Get the m of the requester groups i The estimated position coordinates of the requesting device at the next moment are j’ The corresponding scores between the second alternative roads. For the m of the requester groups i The estimated position coordinates of the requesting device at the next moment are j’ The corresponding scores between the second alternative roads. ' is the normalized second estimated position coordinate to the j’ The shortest distance of the second alternative road. 'For the j’ The connection between the second candidate road and the road where the second estimated position coordinates are located. For the m of the requester groups i The historical moving trajectory direction of the requesting device is j’ The angle fraction of the road direction of the second alternative road. 'For the j’ The road grade score of the second alternative road. is the second distance influencing factor, is the influencing factor of the second connection condition, is the second angle influencing factor, is the second road grade score influencing factor, , , , , .

[0047] Furthermore, by calculating Get the j’ The connection between the second candidate road and the road where the second estimated position coordinates are located. For the j’ The second alternative road and the m of the requester groups iThe shortest number of transit roads required to connect the roads where the requesting devices are located. For example, if the two are directly connected, then ; If there is a road between them, then ; If there are two roads between them, then ; and so on. That is, if the interval between the two s’ road, then .

[0048] Furthermore, by calculating Get the m of the requester groups i The historical moving trajectory direction of the requesting device is j’ The angle fraction of the road direction of the second alternative road.

[0049] in, . For the m of the requester groups i The moving angle of the recent historical moving trajectory of the requesting device, For the m of the requester groups i Requesting devices in t The geographical location coordinates at the time, For the m of the requester groups i Requesting devices in t -1 The geographical location coordinates at the moment, For the j’ The road direction angle of the second alternative road.

[0050] Further, the following method is used to obtain j’ The road grade score of the second alternative road: Get the road grade score of the second alternative road. j’ The road type of the second alternative road is j’ The road type of the second candidate road is searched in the preset data table to find the j’ The road grade score corresponding to the road type of the second candidate road. The corresponding relationship between the road type and the road grade score is stored in the preset data table.

[0051] Furthermore, obtaining a second average value includes: obtaining a matching value between the task type of each requesting device in the requesting party group and the task type of the service device, and calculating the matching value between the task type of each requesting device in the requesting party group and the task type of the service device to obtain a second average value.

[0052] By calculation Get the mThe task type of each requesting device in the requester group is respectively n The average value of the matching value between the task types of service devices, where For the m of the requester groups i The task type of the requesting device is the same as the n The matching value between the task types of the service devices.

[0053] Optionally, the task type includes a computing task type or a content cache type. Obtaining a matching value between the task type of each requesting device in the requesting party group and the task type of the service device includes: obtaining the computing task type of each requesting device in the requesting party group, and obtaining the computing task type of the service device. When the computing task types of the two are the same, the matching value between the task type of each requesting device in the requesting party group and the task type of the service device is 1; otherwise, the matching value between the task type of each requesting device in the requesting party group and the task type of the service device is 0.

[0054] Alternatively, the content cache type of each requesting device in the requesting party group is obtained, and the content cache type of the serving device is obtained. If the content cache types of the two are the same, the matching value between the task type of each requesting device in the requesting party group and the task type of the serving device is 1; otherwise, the matching value between the task type of each requesting device in the requesting party group and the task type of the serving device is 0.

[0055] For example, if m of the requester groups i The computing task type of the requesting device is n The computing tasks of the service devices are of the same type. is 1; otherwise, is 0. For another example, if m of the requester groups i The content cache type of the requesting device is the same as the n The content cache type of each service device is the same. is 1; otherwise, is 0.

[0056] Further, obtaining a third average value includes: obtaining a matching value between the service price borne by each requesting device in the requesting party group and the service price provided by the service device, and calculating the matching value between the service price borne by each requesting device in the requesting party group and the service price provided by the service device to obtain the third average value.

[0057] By calculation Get the m The service price borne by each requesting device in the requesting party group is nThe average value of the matching value between the service prices provided by the service devices, where For the m of the requester groups i The price of the service accepted by the first request device is n The matching value between the service prices provided by the service devices.

[0058] Furthermore, the matching value between the service price borne by each requesting device in the requesting party group and the service price provided by the service device is obtained, including: calculating the preset price range value of the service price borne by each requesting device in the requesting party group and the preset price range value of the service price provided by the service device, and obtaining the matching value between the service price borne by each requesting device in the requesting party group and the service price provided by the service device.

[0059] By calculation Get the m of the requester groups i The price of the service accepted by the first request device is n The matching value between the service prices provided by the service devices.

[0060] in, , . ( For the m of the requester groups i The preset price range of the service price that the requesting device can bear, . For the n The preset price range of the service price for each service device, .

[0061] In one embodiment, the first preset condition is that the matching score is greater than zero. There may be multiple service devices, and the target request device obtains the matching scores between the requester group and each service device, and determines the matching score greater than zero as the target matching score.

[0062] Further, sending a service request to a service device corresponding to the target matching score includes: sorting the target matching scores from large to small, and sending service requests to the service devices corresponding to the sorted target matching scores in sequence. And triggering each service device that receives the service request to obtain a matching index between itself and the requesting party group, and sending feedback information to the target requesting device according to the matching index. The feedback information includes receiving information or rejecting information.

[0063] In another embodiment, the second preset condition is that the received feedback information is the service device with the largest matching score in the received information. The target request device determines the received feedback information as the service device with the largest matching score in the received information as the target server.

[0064] Furthermore, after the service device that sends the feedback information as acceptance information and meets the second preset condition is determined as the target server of all requesting devices in the requesting party group, it also includes: sending confirmation information to the target server.

[0065] Furthermore, before obtaining the matching score between the requester group and the service device, the method further includes: receiving identity information sent by the electronic device. When the received identity information is the target requester device, obtaining the matching score between the requester group and the service device.

[0066] When the mobile device receives the identity information of the target requesting device, it means that the mobile device is the representative of the requesting party group to which it belongs. The target requesting device is matched with each service device, and the target server is determined from each service device for all requesting devices in the requesting party group. In this way, it is not necessary for all requesting devices in the requesting party group to match with each service device, which can reduce the amount of calculation and improve the operation speed.

[0067] After receiving the identity information sent by the electronic device as the target request device, it also includes: receiving the device information of each service device sent by the electronic device, and the device information of other mobile devices in the requester group where the target request device belongs. Among them, the device information includes: device ID, etc.

[0068] Furthermore, after the service device whose feedback information is acceptance information and meets the second preset condition is determined as the target server for all requesting devices in the requesting party group, it also includes: sending the device information of the target server to all requesting devices in the requesting party group where the target requesting device is located, and triggering all requesting devices in the requesting party group to offload computing tasks to the target server.

[0069] In this way, the service device is used as the target server of the requesting device. The requesting device offloads the computing task to the target server, so that the service device processes the computing task for the requesting device. Therefore, the requesting device does not need to offload the computing task to the edge server, which reduces the computing pressure of the edge server.

[0070] Furthermore, after the service device whose feedback information is acceptance information and meets the second preset condition is determined as the target server for all requesting devices in the requesting party group, it also includes: sending the device information of the target server to all requesting devices in the requesting party group where the target requesting device is located, and triggering all requesting devices in the requesting party group to cache the content to be stored to the target server.

[0071] In this way, the service device is used as the target server of the requesting device. The requesting device caches the content to be stored to the target server, so that the service device caches the content to be stored for the requesting device. Therefore, the requesting device does not need to cache the content to be stored to the edge server, which reduces the cache pressure of the edge server.

[0072] Combination Figure 2 As shown, the embodiment of the present disclosure provides a method for determining a target server in a mobile vehicle network, which is applied to a service device, and the service device is a mobile device that can provide services. The mobile device is a vehicle. The method includes: Step S201, when receiving a service request sent by a target requesting device, obtain a matching index between the requesting party group to which the target requesting device belongs and the service device. The requesting party group includes at least one requesting device, the target requesting device is a requesting device in the requesting party group, and the requesting device is a mobile device that needs to be provided with a service. Moreover, the matching score between the requesting party group to which the target requesting device that sends the service request belongs and the service device satisfies a first preset condition.

[0073] Step S202, based on the matching index, feedback information is sent to the target requesting device that sent the service request, and the target requesting device is triggered to set the feedback information as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesting devices in the requesting party group where the target requesting device is located.

[0074] By adopting the method for determining the target server in the mobile vehicle network provided by the embodiment of the present disclosure, the service device can send feedback information to the target request device that sent the service request according to the matching index between the requesting party group to which the target request device that sent the service request belongs and the service device, and trigger the target request device to send the feedback information as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesting devices in the requesting party group. The service device is matched with the requesting device to realize the service device as the target server of the requesting device. It is convenient for the requesting device to offload the computing task or cache the content to the target server, so that the service device can process the computing task or content cache for the requesting device. Thereby, there is no need for the requesting device to offload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server. In addition, since the distance between the mobile devices is short, the communication cost can also be reduced.

[0075] When the mobile device receives the identity information sent by the electronic device as a service device, the service device receives the service request sent by the target request device, and when receiving the service request sent by at least one target request device, obtains the matching index between the requester group where each target request device is located and the service device. The higher the matching index, the more the service device matches the requester group, and the more the service device can provide task computing services or content caching services for all requesting devices in the requester group. The service device sends feedback information to all target requesting devices that have sent service requests to the service device according to the matching index. And trigger the target requesting device to send the feedback information as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesting devices in the requester group where the target requesting device is located. The service device is matched with the requesting device to realize the service device as the target server of the requesting device. Thereby, there is no need for the requesting device to offload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server.

[0076] Further, obtaining the matching index between the requester group where the target requester is located and the service device includes: obtaining a first average value and a fourth average value. The first average value is the average value of the matching values ​​between the movement trajectories of each requester in the requester group and the movement trajectories of the service device. The fourth average value is the average value of the profit rate between the service price borne by each requester in the requester group and the service price provided by the service device. The first average value and the fourth average value are calculated using a second preset algorithm to obtain the matching index between the requester group where the target requester is located and the service device.

[0077] When the service device obtains the matching situation between the requester group where the target requester is located and the service device, the matching situation of the movement track and the matching situation of the price profit rate between each requester in the requester group and the service device is considered. The matching situation between the requester group and each service device can be obtained more accurately. The confirmed target server can match each requester in the requester group.

[0078] Further, obtaining a fourth average value includes: calculating a preset price range value of a service price borne by each requesting device in the requesting party group and a preset price range value of a service price provided by the service device to obtain a fourth average value.

[0079] By calculation The fourth average value is obtained. For the m The service price borne by each requesting device in the requesting party group is n The average of the profitability ratios between the service prices provided by the service equipment. For the m of the requester groups i The preset price range of the service price that the requesting device can bear, . For the n The preset price range of the service price for each service device, .

[0080] Further, the first average value and the fourth average value are calculated using a second preset algorithm to obtain a matching index between the requester group to which the target requesting device belongs and the service device, including: By calculation Get the matching index, where For the m The requester group and n The matching index of each service device. For the m The movement trajectory of each requesting device in the requesting party group is respectively n The average value of the matching value between the mobile trajectories of the service devices, For the m The service price borne by each requesting device in the requesting party group is n The average profit margin between the service prices provided by the service equipment. is the second trajectory impact factor, is the price-profit ratio influencing factor, , , .

[0081] The service request includes a task request and resources required for the task. For example, the task request includes a computing task request or a content cache request. When the service request includes a task computing request, the service request also includes the task computing resources required by all requesting devices in the requesting party group where the target requesting device is located. When the service request includes a content cache request, the service request also includes the cache resources required by all requesting devices in the requesting party group where the target requesting device is located.

[0082] Further, according to the matching index, feedback information is sent to the target request device that sent the service request, including: sorting the matching index from large to small, and sending feedback information to the target request device corresponding to the matching index in sequence according to the sorted matching index. The feedback information includes: acceptance information or rejection information.

[0083] Each time feedback information is sent to the target request device corresponding to the matching index, the following operations are performed: the estimated remaining resources of the service device are obtained, and if the estimated remaining resources are greater than the resources required for the task of the target request device, acceptance information is sent to the corresponding target request device. If the remaining resources are less than or equal to the resources required for the task, rejection information is sent to the corresponding target request device.

[0084] Optionally, obtaining the estimated remaining resources of the service device includes: estimated remaining resources of the service device = current remaining resources - resources required for the task corresponding to the target request device that sent the acceptance information. The current remaining resources are the actual remaining resources of the service device. In this way, it can be ensured that the remaining resources of the service device are greater than the resources requested by the target request device, so as to ensure that there are sufficient resources to provide services to the requesting device.

[0085] Optionally, after the target request device is triggered to feedback information as acceptance information and the service device that meets the second preset condition is determined as the target server for all request devices in the requester group to which the target request device belongs, the method further includes: receiving confirmation information sent by the target request device. When the confirmation information sent by the target request device is received, the service device is confirmed to be the target server for all request devices in the requester group to which the target request device that sent the confirmation information belongs.

[0086] Combination Figure 3 As shown, an embodiment of the present disclosure provides a method for determining a target server in a mobile vehicle network, which is applied to an electronic device. The electronic device includes a computer, a server, or a base station. The method includes: Step S301, obtaining device power, device capabilities and service prices of at least two mobile devices.

[0087] Step S302: Calculate the device power, device capability and service price of each mobile device using a third preset algorithm to obtain an identity evaluation score of each mobile device.

[0088] Step S303: determining the identity information of the corresponding mobile device according to the identity evaluation score of each mobile device.

[0089] Step S304, when the identity information is a service device, the service device identity information is sent to the corresponding mobile device, triggering the service device to receive the service request sent by the target request device, and obtaining the matching index between the requester group to which the target request device belongs and the service device, and sending feedback information to the target request device based on the matching index; when the identity information is a requester device, clustering operations are performed on each requester device to obtain at least one requester group; according to preset rules, one requester device is selected from each requester group, and the identity information of the selected requester device is determined as the target requester; the target requester identity information is sent to the corresponding requester device, triggering the target requester device to obtain the matching score between the corresponding requester group and the service device, and triggering the target requester device to receive the feedback information sent by the service device, and the sent feedback information is determined as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesters in the corresponding requester group.

[0090] By adopting the method for determining the target server provided by the embodiment of the present disclosure, the electronic device divides multiple mobile devices into two categories, namely, requesting devices and service devices, according to the device power, device capabilities and service prices of each mobile device, and triggers the requesting device to match with the service device, thereby realizing that the service device is used as the target server of the requesting device. It is convenient for the requesting device to offload the computing task or cache the content to the target server, so that the service device can process the computing task or content cache for the requesting device. Therefore, there is no need for the requesting device to offload the computing task or cache the content to the edge server, thereby reducing the working pressure of the edge server. At the same time, the service device provides computing tasks or content cache for the requesting device, and the distance between the devices is short, which can also reduce the communication cost.

[0091] Furthermore, the third preset algorithm is used to calculate the device power, device capability and service price of each mobile device to obtain the identity evaluation score of each mobile device, including: By calculation Get the identity assessment score of the mobile device. For the z The identity assessment score of each mobile device, For the z The device power of each mobile device, , For the z device capabilities of each mobile device, , For the z The price of service provided by a mobile device, , , , , .

[0092] In some embodiments, the device capability includes the device computing capability or the device storage capability. When the mobile devices are classified according to whether they can provide computing services, the identity evaluation score of each mobile device is obtained by calculating the device power, device computing capability and service price of the mobile device, so that the mobile devices are divided into requesting devices and serving devices according to the identity evaluation score. The requesting device is a mobile device that needs to be provided with computing services, that is, the requesting device needs to offload the computing tasks to the server. The serving device is a mobile device that can provide computing services.

[0093] In another embodiment, when mobile devices are classified according to whether they can provide cache services, the identity evaluation score of each mobile device is calculated by the device power, device storage capacity and service price of the mobile device, so that the mobile devices are divided into requesting devices and serving devices according to the identity evaluation score. The requesting device is a mobile device that needs to be provided with a cache service, that is, the requesting device needs to cache the content to the server. The serving device is a mobile device that can provide a cache service.

[0094] Furthermore, the identity information of the corresponding mobile device is determined based on the identity evaluation score of each mobile device, including: when the identity evaluation score is greater than or equal to the set value, the identity information of the mobile device corresponding to the identity evaluation score is determined as a service device. When the identity evaluation score is less than the set value, the identity information of the mobile device corresponding to the identity evaluation score is determined as a requesting device. For example, the set value is 1.5. When the identity evaluation score of the mobile device reaches 1.5, it means that the mobile device can provide services to other mobile devices. Then the mobile device greater than or equal to the set value is determined as a service device, so that the service device can better meet the needs of the requesting device when providing services to the requesting device.

[0095] Furthermore, clustering operations are performed on each requesting device, including: clustering each requesting device using a k-means clustering method.

[0096] Specifically, K requesting devices are randomly selected as the initial centroids of K requesting party groups. The distances of each requesting device from the initial centroid are calculated, and each requesting device is assigned to the requesting party group to which the centroid closest to the requesting device belongs. The mean of all requesting devices in each requesting party group is then used as the new centroid. When the predetermined number of iterations is reached, the iteration is stopped. Each requesting party group is obtained.

[0097] The distance between each requesting device and the initial centroid is obtained in the following way: calculate Get the a The requesting device and b The distance between the requesting devices. For the a The requesting device and b The distance between the requesting devices, For the a The requesting device and b The movement angle of the requesting device, For the a The task type of the requesting device is the same as the b The matching value between the task types of the requesting devices, For the a The price of the service accepted by the first request device is b The matching value between the service prices afforded by the requesting devices, For the a The movement trajectory of the requesting device is b The matching value between the moving trajectories of the requesting devices, is the moving angle influence factor, is the task type influencing factor, To withstand the factors affecting service prices, is the third trajectory impact factor, , , , , .

[0098] Furthermore, by calculating Get the a The requesting device and b The movement angle of the requesting device, where , For the a Requesting devices in t The geographical location coordinates at the time, For the a Requesting devices in t -1 The geographical location coordinates at the moment, For theb Requesting devices in t The geographical location coordinates at the time, For the b Requesting devices in t -1 The geographic location coordinates at time. For the a The moving angle of the recent historical moving trajectory of the requesting device, For the b The moving angle of the most recent historical moving trajectory of the requesting device.

[0099] In some embodiments, the computing task type of each requesting device is obtained, and in the a The computing task type of the requesting device is b When the computing task types of the requesting devices are the same, is 1; otherwise, is 0. For another example, the content cache type of each requesting device is obtained. a The content cache type of the requesting device is the same as the b If the content cache type of the requesting devices is the same, is 1; otherwise, is 0.

[0100] Furthermore, the preset price range value of the service price to be borne by each requesting device is calculated to obtain the matching value between the service prices to be borne by each requesting device.

[0101] By calculation Get the a The price of the service accepted by the first request device is b The matching value between the service prices that the requesting devices can bear. , . For the a The preset price range of the service price that the requesting device can bear, . For the b The preset price range of the service price that the requesting device can bear, .

[0102] Furthermore, the historical position coordinates and the predicted position coordinates at the next moment of each requesting device are obtained, and the historical position coordinates and the predicted position coordinates at the next moment of each requesting device are calculated to obtain the matching value between the movement trajectories of each requesting device.

[0103] By calculation Get the a The movement trajectory of the requesting device is bThe matching value between the moving trajectories of the requesting devices. is the number of coordinate points of the moving trajectory of the requesting device, and the number of coordinate points of the moving trajectory of each requesting device is the same. For the a Requesting devices in The historical position coordinates at the time, For the b Requesting devices in The historical position coordinates at the time, ( ) indicates the calculation of a The requesting device and b Requesting devices in The distance between the historical position coordinates at the time, For the a The predicted location coordinates of the requesting device at the next moment, For the b The predicted location coordinates of the requesting device at the next moment, Indicates the calculation a The requesting device and b The distance between the predicted location coordinates of the requesting devices at the next moment.

[0104] Furthermore, the preset position coordinates of the requesting device at the next moment are obtained by: obtaining the historical movement trajectory of the requesting device. Inputting the historical movement trajectory of the requesting device into the preset neural network to obtain the estimated position coordinates of the requesting device at the next moment. Correcting the estimated position coordinates of the requesting device at the next moment to obtain the predicted position coordinates of the requesting device at the next moment. The preset neural network is a neural network based on LSTM-Attention.

[0105] Furthermore, the estimated position coordinates of the requesting device at the next moment are corrected, including: determining all roads within a preset radius with the estimated position coordinates of the requesting device at the next moment as the center as three alternative roads, and obtaining the road data of the third alternative road. According to the road data of each third alternative road, obtain the corresponding scores between the estimated position coordinates of the requesting device at the next moment and each third alternative road. Determine the third alternative road corresponding to the maximum corresponding score as the third target road. Determine the coordinates of the point on the third target road that is closest to the third estimated position coordinates as the predicted position coordinates of the requesting device at the next moment. Among them, the third estimated position coordinates are the estimated position coordinates of the requesting device at the next moment.

[0106] Further, according to the road data of each third candidate road, obtaining the corresponding score between the estimated position coordinates of the requesting device at the next moment and each third candidate road includes: calculating Get the estimated position coordinates of the requesting device at the next moment and the p The corresponding scores between the third alternative roads. For the o The estimated position coordinates of the requesting device at the next moment are p o is the number of requested devices, a ≤ o, b ≤ o . '' is the normalized third estimated position coordinate to the p The shortest distance of the third alternative road. For the p The connection between the third alternative road and the road where the third estimated position coordinates are located. For the o The historical moving trajectory direction of the requesting device is p The angle fraction of the road direction of the third alternative road. ''For the p The road grade score of the third alternative road. is the third distance influence factor, is the third connection status influencing factor, is the third angle influencing factor, is the third road grade score influencing factor, , , , , .

[0107] Furthermore, by calculating Get the p The connection between the third candidate road and the road where the third estimated position coordinates are located. For the p The third alternative and o The shortest number of transit roads required to connect the roads where the requesting devices are located. For example, if the two are directly connected, then =0; if there is a road between them, then =1; if there are two roads between them, then =2; and so on. That is, if the p The third alternative and o The distance between the roads where the requested devices are located road, then .

[0108] Furthermore, by calculating Get the oThe historical moving trajectory direction of the requesting device is p The angle fraction of the road direction of the third alternative road.

[0109] in, . For the o The moving angle of the recent historical moving trajectory of the requesting device, For the o Requesting devices in t The geographical location coordinates at the time, For the o Requesting devices in t -1 The geographical location coordinates at the moment, For the p The road direction angle of the third alternative road.

[0110] Further, the following method is used to obtain p The road grade score of the third alternative road: p The road type of the third alternative road is searched in a preset data table to find the p The road grade score corresponding to the road type of the third candidate road. The corresponding relationship between the road type and the road grade score is stored in the preset data table.

[0111] After clustering the requesting devices to obtain at least one requesting party group, a requesting device is selected from each requesting party group according to a preset rule, and the selected requesting device is determined as the target requesting device. The preset rule is to select the requesting device with the largest power from the requesting party group. Alternatively, the preset rule is to select the requesting device with the strongest computing power from the requesting party group. Alternatively, the preset rule is to select the requesting device with the most central position from the requesting party group.

[0112] Combination Figure 4 As shown, the embodiment of the present disclosure provides a method for determining a target server, including: Step S401, the electronic device obtains the device power, device computing capacity and service price of multiple mobile devices.

[0113] In step S402, the electronic device calculates the device power, device computing capability and service price of each mobile device using a third preset algorithm to obtain an identity evaluation score of each mobile device.

[0114] Step S403, determining the identity information of the corresponding mobile device according to the identity evaluation score of each mobile device, and executing step S404 if the identity information is a service device; and executing step S405 if the identity information is a requesting device.

[0115] Step S404: the electronic device sends the service device identity information to the corresponding mobile device.

[0116] Step S405: the electronic device performs clustering operation on each requesting device to obtain at least one requesting party group; selects a requesting device from each requesting party group according to a preset rule, and determines the identity information of the selected requesting device as the target requesting device. Then, step S406 is executed.

[0117] Step S406: The electronic device sends the target requesting device identity information to the corresponding requesting device.

[0118] Step S407, the target requesting device obtains the matching score between the requesting party group to which it belongs and the service device. The target requesting device calculates the historical position coordinates, predicted position coordinates at the next moment, calculation task type, and preset price interval value of the service price of each requesting device in the requesting party group, and the historical position coordinates, predicted position coordinates at the next moment, calculation task type, and preset price interval value of the service price of the service device, and obtains the matching score between the requesting party group to which it belongs and the service device.

[0119] Step S408: The target requesting device determines the matching score that meets the first preset condition as the target matching score.

[0120] Step S409: the target requesting device sends a service request to the service device corresponding to the target matching score.

[0121] Step S410, when receiving the service request sent by the target request device, the service device obtains the matching index between the requester group to which the target request device belongs and the service device. The service device calculates the historical position coordinates, the predicted position coordinates at the next moment, and the preset price interval value of the service price of each requester in the requester group, and the historical position coordinates, the predicted position coordinates at the next moment, and the preset price interval value of the service price of the service device, to obtain the matching index between the requester group to which the target request device belongs and the service device.

[0122] Step S411: The service device sends feedback information to the target request device according to the matching index.

[0123] Step S412: The target requesting device determines the service device that has sent the acceptance information and meets the second preset condition as the target server for all requesting devices in the requesting party group.

[0124] Step S413, the target requesting device sends confirmation information to the service device determined as the target server. The target requesting device sends the device information of the target server to other requesting devices in the requesting party group, and triggers all requesting devices in the requesting party group to offload computing tasks to the target server.

[0125] In this way, by classifying mobile devices and clustering requesting devices, multiple requesting party groups are obtained. Representatives in the requesting party groups are matched with service devices. This enables mobile devices to autonomously offload tasks to each other, reduces the computing and transmission pressure of edge servers, reduces device resource consumption and reduces costs.

[0126] By using the method for determining the target server of the embodiment of the present disclosure, in the Internet of Vehicles, mobile vehicles are classified to obtain requesting devices and service devices. Among them, the requesting device is a mobile vehicle that needs task offloading. The service device is a mobile vehicle that can provide computing tasks for other mobile vehicles. Then, the requesting devices are clustered to obtain multiple requesting party groups. The representative in the requesting party group, that is, the target requesting device is matched with the service device. Thereby, the target server is determined for the requesting device in the requesting party group. In this way, it is achieved that mobile vehicles with strong computing power provide computing tasks for mobile vehicles that need task offloading. Not only does it reduce the computing pressure of the edge server. In addition, the distance between the mobile vehicles is short, the communication effect is better, and the communication cost is lower.

[0127] Combination Figure 5 As shown, the embodiment of the present disclosure provides a method for determining a target server, including: Step S501, the electronic device obtains the device power, device storage capacity and service price of multiple mobile devices.

[0128] Step S502: The electronic device calculates the device power, device storage capacity and service price of each mobile device using a third preset algorithm to obtain an identity evaluation score of each mobile device.

[0129] Step S503, determining the identity information of the corresponding mobile device according to the identity evaluation score of each mobile device, and executing step S504 when the identity information is a service device; and executing step S505 when the identity information is a requesting device.

[0130] Step S504: the electronic device sends the service device identity information to the corresponding mobile device.

[0131] Step S505: the electronic device performs clustering operation on each requesting device to obtain at least one requesting party group; selects a requesting device from each requesting party group according to a preset rule, and determines the identity information of the selected requesting device as the target requesting device. Then, step S506 is executed.

[0132] Step S506: the electronic device sends the target requesting device identity information to the corresponding requesting device.

[0133] Step S507, the target requesting device obtains the matching score between the requesting party group to which it belongs and the service device. The target requesting device calculates the historical location coordinates, predicted location coordinates at the next moment, content cache type, and preset price range of the service price of each requesting device in the requesting party group, and the historical location coordinates, predicted location coordinates at the next moment, content cache type, and preset price range of the service price of the service device, to obtain the matching score between the requesting party group to which it belongs and the service device.

[0134] Step S508: The target requesting device determines the matching score that meets the first preset condition as the target matching score.

[0135] Step S509: the target requesting device sends a service request to the service device corresponding to the target matching score.

[0136] Step S510: When receiving the service request sent by the target request device, the service device obtains the matching index between the requester group to which the target request device belongs and the service device. The service device calculates the historical position coordinates, the predicted position coordinates at the next moment, and the preset price interval value of the service price of each requester in the requester group, and the historical position coordinates, the predicted position coordinates at the next moment, and the preset price interval value of the service price of the service device, to obtain the matching index between the requester group to which the target request device belongs and the service device.

[0137] Step S511: The service device sends feedback information to the target request device according to the matching index.

[0138] Step S512: The target requesting device determines the service device that has sent the acceptance information and meets the second preset condition as the target server for all requesting devices in the requesting party group.

[0139] Step S513, the target requesting device sends confirmation information to the service device determined as the target server. The target requesting device sends the device information of the target server to other requesting devices in the requesting party group, and triggers all requesting devices in the requesting party group to cache content to the target server.

[0140] In this way, by classifying mobile devices and clustering requesting devices, multiple requesting party groups are obtained. Representatives in the requesting party groups are matched with service devices. This enables mobile devices to autonomously cache and read content from each other, reducing the cache and transmission pressure of edge servers, reducing device resource consumption and reducing costs.

[0141] By using the method for determining the target server of the embodiment of the present disclosure, in the Internet of Vehicles, mobile vehicles are classified to obtain requesting devices and service devices. Among them, the requesting device is a mobile vehicle that needs content caching. The service device is a mobile vehicle that can provide content caching for other mobile vehicles. Then, the requesting devices are clustered to obtain multiple requesting party groups. The representative in the requesting party group, that is, the target requesting device is matched with the service device. Thereby, the target server is determined for the requesting device in the requesting party group. In this way, it is achieved that mobile vehicles with strong storage capabilities provide caching services for mobile vehicles that need content caching. Not only does it reduce the storage pressure of the edge server. In addition, the distance between the mobile vehicles is short, the communication effect is better, and the communication cost is lower.

[0142] In some embodiments, if there is a requester class group that is not assigned to a service device, and the number of cycles is less than a preset number of cycles, In the case of, the target requesting device that is not assigned to the requesting party group of the service device continues to calculate the matching score with the service device and sends the service request according to the matching score. Otherwise, the edge server with the closest geographical location and guaranteed service resources is selected as the target server.

[0143] Combination Figure 6 As shown, an embodiment of the present disclosure provides a target request device 600, including a first processor (processor) 604 and a first memory (memory) 601 storing program instructions. Optionally, the target request device may also include a first communication interface (Communication Interface) 602 and a first bus 603. Among them, the first processor 604, the first communication interface 602, and the first memory 601 can communicate with each other through the first bus 603. The first communication interface 602 can be used for information transmission. The first processor 604 can call the program instructions in the first memory 601 to execute the method for determining the target server of the above embodiment.

[0144] In addition, the program instructions in the first memory 601 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0145] The first memory 601 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The first processor 604 executes the function application and data processing by running the program instructions / modules stored in the first memory 601, that is, implementing the method for determining the target server in the above embodiment.

[0146] The first memory 601 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the first memory 601 may include a high-speed random access memory and may also include a non-volatile memory.

[0147] Combination Figure 7 As shown, an embodiment of the present disclosure provides a service device 700, including a second processor (processor) 704 and a second memory (memory) 701 storing program instructions. Optionally, the target request device may also include a second communication interface (Communication Interface) 702 and a second bus 703. Among them, the second processor 704, the second communication interface 702, and the second memory 701 can communicate with each other through the second bus 703. The second communication interface 702 can be used for information transmission. The second processor 704 can call the program instructions in the second memory 701 to execute the method for determining the target server of the above embodiment.

[0148] In addition, the program instructions in the second memory 701 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0149] The second memory 701 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The second processor 704 executes the function application and data processing by running the program instructions / modules stored in the second memory 701, that is, implementing the method for determining the target server in the above embodiment.

[0150] The second memory 701 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the second memory 701 may include a high-speed random access memory and may also include a non-volatile memory.

[0151] Combination Figure 8As shown, an embodiment of the present disclosure provides an electronic device 800, including a third processor (processor) 804 and a third memory (memory) 801 storing program instructions. Optionally, the target request device may also include a third communication interface (Communication Interface) 802 and a third bus 803. Among them, the third processor 804, the third communication interface 802, and the third memory 801 can communicate with each other through the third bus 803. The third communication interface 802 can be used for information transmission. The third processor 804 can call the program instructions in the third memory 801 to execute the method for determining the target server of the above embodiment.

[0152] In addition, the program instructions in the third memory 801 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0153] The third memory 801 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The third processor 804 executes the function application and data processing by running the program instructions / modules stored in the third memory 801, that is, implementing the method for determining the target server in the above embodiment.

[0154] The third memory 801 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the third memory 801 may include a high-speed random access memory and may also include a non-volatile memory.

[0155] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes, or a transient storage medium.

[0156] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, method or device including the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0157] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0158] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for determining a target server in a mobile vehicle network, characterized in that: Applied to a target requesting device, the target requesting device is a requesting device in a requesting party group, the requesting party group includes at least one requesting device, and the requesting device is a mobile device that needs to be provided with a service, the method includes: Obtaining a matching score between the requester group and a service device; wherein the service device is a mobile device capable of providing a service; Determining a matching score that satisfies a first preset condition as a target matching score; Sending a service request to a service device corresponding to the target matching score, triggering the service device to send feedback information to the target requesting device; The feedback information sent by the service device is received, and the feedback information sent is regarded as acceptance information. The service device that meets the second preset condition is determined as the target server of all requesting devices in the requesting party group.

2. The method according to claim 1, characterized in that Get the matching score between the requester group and the service device, including: Obtain a first average value, a second average value, and a third average value, wherein the first average value is the average value of the matching values ​​between the movement trajectory of each requesting device in the requesting party group and the movement trajectory of the service device, the second average value is the average value of the matching values ​​between the task type of each requesting device in the requesting party group and the task type of the service device, and the third average value is the average value of the matching values ​​between the service price borne by each requesting device in the requesting party group and the service price provided by the service device; The first average value, the second average value, and the third average value are calculated using a first preset algorithm to obtain a matching score between the requester group and the service device.

3. The method according to claim 1, characterized in that: Before obtaining the matching score between the requester group and the service device, it also includes: Receiving identity information sent by an electronic device; In the case where the identity information is a target requesting device, a matching score between the requesting party group and the serving device is obtained.

4. The method according to claim 1 or 2, characterized in that: After the service device whose feedback information is acceptance information and meets the second preset condition is determined as the target server of all requesting devices in the requesting party group, the method further includes: Triggering all requesting devices in the requester group to offload computing tasks to the target server; or, All requesting devices in the requesting party group are triggered to cache the content to be stored to the target server.

5. A method for determining a target server in a mobile vehicle network, characterized in that: Applied to a service device, the service device is a mobile device capable of providing services, the method comprising: In the case of receiving a service request sent by a target requesting device, obtaining a matching index between the requesting party group to which the target requesting device belongs and the service device; wherein the requesting party group includes at least one requesting device, the target requesting device is a requesting device in the requesting party group, and the requesting device is a mobile device that needs to be provided with a service; According to the matching index, feedback information is sent to the target requesting device, and the target requesting device is triggered to determine the service device whose feedback information is acceptance information and meets the second preset condition as the target server for all requesting devices in the requesting party group.

6. The method according to claim 5, characterized in that Obtaining a matching index between the requester group to which the target requesting device belongs and the service device, including: Obtaining a first average value and a fourth average value, wherein the first average value is an average value of matching values ​​between the movement trajectories of each requesting device in the requesting party group and the movement trajectories of the service device, and the fourth average value is an average value of the profit rate between the service price borne by each requesting device in the requesting party group and the service price provided by the service device; The first average value and the fourth average value are calculated using a second preset algorithm to obtain a matching index between the requesting party group to which the target requesting device belongs and the service device.

7. A method for determining a target server in a mobile vehicle network, characterized in that: Applied to electronic equipment, the method comprises: Obtaining device power, device capabilities, and service prices of at least two mobile devices; Calculate the device power, device capability and service price of each mobile device using a third preset algorithm to obtain an identity evaluation score of each mobile device; Determining identity information of the corresponding mobile device according to the identity evaluation score of each mobile device; In the case where the identity information is a service device, the service device identity information is sent to the corresponding mobile device, triggering the service device to receive the service request sent by the target request device, and obtaining the matching index between the requester group to which the target request device belongs and the service device, and sending feedback information to the target request device according to the matching index; In the case where the identity information is a requesting device, a clustering operation is performed on each requesting device to obtain at least one requesting party group; a requesting device is selected from each requesting party group according to a preset rule, and the identity information of the selected requesting device is determined as a target requesting device; the identity information of the target requesting device is sent to a corresponding requesting device, triggering the target requesting device to obtain a matching score between the corresponding requesting party group and the service device, and triggering the target requesting device to receive feedback information sent by the service device, and the sent feedback information is regarded as acceptance information, and the service device that meets the second preset condition is determined as the target server for all requesting devices in the requesting party group.

8. A target request device, characterized in that: include: A first processor and a first memory storing first program instructions, wherein the first processor is configured to execute the method for determining a target server according to any one of claims 1 to 4 when running the first program instructions.

9. A service device, characterized in that: include: A second processor and a second memory storing second program instructions, wherein the second processor is configured to execute the method for determining a target server according to claim 5 or 6 when running the second program instructions.

10. An electronic device, characterized in that: include: A third processor and a third memory storing third program instructions, wherein the third processor is configured to execute the method for determining a target server according to claim 7 when running the third program instructions.

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