A content distribution method based on incentive mechanism in a blind area of a highway of internet of vehicles

Abstract

The application discloses a content distribution method based on an incentive mechanism in a highway blind area of Internet of Vehicles, and the method comprises the following steps: exchanging the speed, position, requested content and possessed content block information between vehicles to form an initial cluster set; calculating the optimal content transmission benefit in the cluster based on an incentive factor; and performing alliance game based on the incentive mechanism to obtain the optimal clustering mode, so that the optimal content distribution method in the highway blind area of Internet of Vehicles is obtained. The application can help the vehicle to obtain the requested content with lower download delay and lower download incomplete rate, and improve the service quality of content distribution in the highway blind area of Internet of Vehicles.

Description

Technical Field

[0001] This invention belongs to the field of vehicle-to-everything (V2X) content distribution, and more specifically, relates to an incentive-based content distribution method for V2X highway blind spots. Background Technology

[0002] With the development of communication technology, content distribution in the Internet of Vehicles (IoV) is no longer limited to simple warning information. Road condition information, weather information, and even entertainment information such as news, advertisements, and short videos have become the main content to be distributed. IoV users hope to obtain the content they need faster and more reliably for a better experience. However, in IoV scenarios, especially on highways, the high mobility of vehicles, unstable channels, and high deployment costs limit the number of Road Side Units (RSUs), making it difficult for vehicles to obtain complete content directly from RSUs and base stations. Therefore, it is necessary to utilize vehicle caching and V2V (Vehicle-to-Vehicle) communication to help vehicles obtain the required content from other vehicles in blind spots, reducing download latency and failure rates.

[0003] Current research has explored content distribution methods for connected vehicles, but most studies focus solely on minimizing the time required for a single distribution and maximizing the number of vehicles receiving their desired content. These methods either fail to consider how to incentivize vehicle participation in content distribution, including selfish vehicles that only want to download content, or how to ensure each distribution positively impacts subsequent distributions. This leads to poor performance in connected highways with long blind spots and high traffic volumes, resulting in lower download latency and incompleteness rates. Addressing content distribution issues in blind spots on connected highways requires both incentivizing active vehicle participation and determining the optimal content distribution method to improve service quality. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a content distribution method based on an incentive mechanism in the blind spots of the Internet of Vehicles highway, which incentivizes vehicles to spontaneously participate in content distribution and reduces the latency and incompleteness of vehicle content downloads.

[0005] To achieve the above-mentioned objectives, this invention provides a content distribution method based on an incentive mechanism in the blind spots of highways connected by vehicles, comprising the following steps:

[0006] S1: Calculate the set of transferable vehicles for each vehicle within the blind zone:

[0007] The current collection of all vehicles in the blind spot of the connected vehicle highway is as follows N is the total number of vehicles in the blind spot, V i For the vehicle with ID i in the blind spot; V for each vehicle in the blind spot i V, exchanges information with nearby vehicles and calculates the set of transmissible vehicles Near. i And broadcast Near i ;

[0008] S2: Calculate the maximum node transition value within the cluster at round t based on the incentive factor:

[0009] S2.1: Calculate the efficiency of content transfer between nodes within a cluster:

[0010] Before the start of the t-th round of the coalition game, the set of clusters is: For any cluster ,vehicle Cluster head, number of cluster members ,in, Represents the set of cluster head nodes. Represents a set The number of elements in the cluster; for any vehicle V within the cluster i If from other vehicles within the cluster Obtain a content block at [location]. This behavior is recorded as Then the receiving vehicle V i and the sending vehicle V j The content transfer benefits brought to the cluster are as follows: and The calculation is as follows:

[0011]

[0012]

[0013] in, Indicates in transmission behavior In the middle, the receiving vehicle V i Is the retrieved content block x the desired content block? , indicating vehicle V i Able to obtain the required content block, This indicates that vehicle V i Unable to obtain the required content block; Indicates in transmission behavior In the middle, the sending vehicle V j Is it possible to distribute content blocks to other vehicles? This indicates that other vehicles are able to access V. j Download or cache content block x, Indicates vehicle V jCannot provide content blocks to other vehicles; coefficient a i and b j This is an incentive factor designed to encourage vehicles to spontaneously participate in the distribution process; the calculation method is as follows:

[0014]

[0015]

[0016] Among them, c (i) c (j) and c (k) These represent vehicle V. i V j V k The contribution score is the sum of the historical number of times a vehicle performs distribution actions within the highway blind spot. Distribution actions include caching non-requested content blocks and providing content blocks to other vehicles; V i V j V k All belong to And V i Not equal to V j ; It is a smoothing factor;

[0017] S2.2: Calculate the content distribution preference for each vehicle within the cluster:

[0018] Calculate vehicle V i From other vehicles within the cluster Download a content block Maximum content delivery efficiency :

[0019]

[0020] in, It is vehicle V j The existing set of content blocks; since the vehicle cannot download new content blocks from itself, therefore If vehicle V j Not in V i Near the set of transferable vehicles i middle, For vehicle V i Its content distribution trend i The difference between the average benefit of a vehicle as a receiver and the average benefit of a vehicle as a sender is calculated as follows:

[0021]

[0022] in, The cluster represents the cluster at the start of the t-th round of the game. Number of vehicles in China;

[0023] S2.3: Calculate the optimal content distribution scheme and maximum content delivery efficiency within each cluster:

[0024] cluster Inside The vehicle nodes are sorted from largest to smallest according to their distribution preference and assigned a cluster number: ,in, For sorted clusters Vehicle numbered i; create a matrix H* that stores the maximum content transfer efficiency between vehicles, where the element in the i-th row and j-th element is... Indicates vehicle With vehicles To maximize the efficiency of content transmission, the calculation method for the elements in the matrix is ​​as follows:

[0025]

[0026] in, , Representing vehicles from Download a content block and a vehicle from The maximum content transfer benefit that downloading a content block brings to a cluster is calculated by S2.2; cluster The set of all possible distribution schemes is represented as Among them, the scheme { }, Indicates vehicle and Content blocks are distributed between them. Number of connections | | Satisfies constraints That is, the number of connections must not exceed half the number of vehicles within the cluster; among which Indicates to / 2 rounds down; any connection Benefits Let be the element value corresponding to the i-th row and j-th column of matrix H*;

[0027] Regarding the plan Total efficiency of intra-cluster content transmission The sum of the benefits of all connections within the cluster is calculated as follows:

[0028]

[0029] For clusters Selection of the optimal content distribution scheme within the cluster, and the overall efficiency of optimal content delivery within the cluster. For a set of distribution schemes The objective function for calculating the maximum content transfer efficiency within a cluster is: (This is the sum of the benefits of all possible solutions.)

[0030]

[0031]

[0032] Among them, constraint (1) Representation scheme China Vehicle Whether or not they are assigned to participate in content distribution Representation scheme China Vehicle Not assigned to participate in content distribution Representation scheme China Vehicle The content is distributed to other vehicles; constraint (2) indicates that the number of connections in each scheme does not exceed the total number of vehicles in the cluster. Half of; constraint (3) indicates that the benefit of the content transferred between the two vehicles is greater than 0; constraint (4) indicates that the benefit of the content transferred between the two vehicles is greater than 0. Vehicles that transmit content Must be in the vehicle In the set of transferable vehicles, Cluster Vehicle with internal number i A collection of transferable vehicles;

[0033] Calculate and obtain clusters The optimal intra-cluster distribution scheme is The maximum transmission efficiency is The set of vehicles not scheduled to participate in optimal cluster content transmission is , ;

[0034] S2.4: Calculate the maximum intra-cluster node transition value for each cluster:

[0035] For clusters According to the optimal content distribution scheme sought in S2.3 The set of vehicles not scheduled to participate in optimal cluster content transmission is Calculate vehicle nodes The transfer value is calculated as follows:

[0036] When vehicle node From cluster Transfer to vehicles Clusters with cluster heads Then, a new cluster is formed. , Then the value of that node is transferred. for:

[0037]

[0038] in, To increase the benefits brought about by transferring this node, and These are the newly formed clusters and Maximum content delivery efficiency and They are clusters and The maximum content delivery efficiency; It is the cost of moving that node, determined by the game round number t and the target node. Current number of members | Decision It is a cost coefficient;

[0039] Computational clusters Maximum node transfer value within the cluster The method is as follows:

[0040]

[0041] Satisfy the maximum transfer value The corresponding node is , ;

[0042] S3: Calculate the optimal clustering method and optimal intra-cluster content distribution scheme based on the incentive mechanism:

[0043] Based on the initial cluster set The optimal clustering method is obtained by conducting a coalition game and calculating the maximum node transition value within a cluster based on S2.4, until the maximum node transition value within all clusters is less than zero. T represents the number of rounds of coalition game played to reach Nash equilibrium; the cluster head node of each cluster calculates and obtains the optimal content distribution scheme within the cluster based on the method in S2.3;

[0044] S4: Transfer content blocks and update contribution using the optimal intra-cluster content distribution scheme:

[0045] After obtaining the optimal clustering method and the optimal intra-cluster content distribution scheme based on the method in S3, the cluster head node of each cluster arranges content transmission between intra-cluster nodes through broadcasting. After the transmission is completed, the transmission results of vehicles within the cluster are collected, and the vehicle contribution is updated according to the results.

[0046] For any cluster in the final clustering Optimal distribution scheme within the cluster In the middle, vehicles , From another vehicle Download content x here, x A m,j , where A m,j It is a vehicle If the set of content blocks already owned is given, then this behavior is denoted as If the content block is successfully transmitted, the cluster head vehicle updates the vehicle. Contribution c (m,i) and vehicles Contribution c (m,j) The update method is as follows:

[0047]

[0048] .

[0049] As a further optimization of the present invention, the calculation of the set of transportable vehicles in step S1 is determined by the following method:

[0050] Each vehicle V i V broadcasts its own directional speed, v, to nearby vehicles. i Location pos i Request content r i The set of content blocks owned is A i ={D i C i}, and its own contribution level c (i) Information; of which, D i For vehicle V i The set of requested content blocks that have been downloaded, C i This is a cached collection of content blocks not requested by the vehicle itself; after exchanging relevant information, vehicle V... i For other vehicles within the communication range V j ∈V computational communication duration :

[0051]

[0052] Where R represents the vehicle's communication range, determined based on the signal-to-noise ratio threshold of the vehicle's received signal; for each piece of content, it is divided into content blocks of equal size for transmission, with each content block having a size of M. b Vehicle V i By calculation, it can be determined whether it is related to other vehicles V. j V's communication duration Does it meet the following conditions:

[0053]

[0054] If the condition is satisfied, it indicates that vehicle V i and vehicle V j have enough communication time to stably transmit one content block; wherein, represents the transmission rate of communication between vehicle V i and V j ; is a time margin parameter set to prevent transmission failure caused by unstable channel or excessive calculation time, which is determined according to the time taken for the vehicle to finally form a cluster in simulation or test; for vehicle V i , the set of vehicles satisfying the sustainable communication time condition is Near i .

[0055] As a further optimization solution of the present invention, selecting the optimal intra-cluster distribution scheme in step S2.3 is determined by the following method:

[0056] The method for selecting the optimal intra-cluster distribution scheme for each cluster is: in matrix H*, find any element greater than 0 , then set all elements in the i-th row, the i-th column, the j-th row, and the j-th column to zero, then find the next element greater than 0 until all elements are set to zero, so that the sum of the selected elements is maximized, which is the maximum transmission benefit, and the connected set corresponding to the plurality of selected elements at this time is the optimal intra-cluster distribution scheme ;

[0057] The selection process is as follows:

[0058] 1) A greedy search algorithm is used on the matrix H* to find a local optimal solution and incorporate it into the solution set ;

[0059] 2) Set the solution sequence number k=2;

[0060] 3) Set the row number i=1;

[0061] 4) Set the column number j= ;

[0062] 5) Under the condition of satisfying the constraint of calculating the maximum transmission benefit, for each solution in the solution set , replace the vehicle that performs content transmission with vehicle with vehicle , retain all connections including vehicles satisfying lb<i in the solution , where lb is the vehicle in the cluster​ The remaining connections are obtained by sorting the sequence numbers and using a greedy search. The set of these connections is the new solution. ;

[0063] 6) If set If yes, proceed to step 7); otherwise, proceed to step 8).

[0064] 7) k = k + 1, and the new scheme Incorporation scheme set middle;

[0065] 8) j = j + 1, if j < (Return to step 5); otherwise, proceed to step 9).

[0066] 9) i=i+1, if i< (Return to step 4); otherwise execute step 10).

[0067] 10) For the set of solutions For each scheme, calculate the total benefit; the scheme with the largest total benefit is the cluster. Optimal content distribution scheme within the cluster The corresponding total benefits That is, a cluster Maximum content transfer efficiency within the cluster;

[0068] Optimal intra-cluster distribution scheme In this context, the set of vehicles not scheduled to participate in optimal intra-cluster content transmission is: , , The calculation is as follows:

[0069]

[0070] in, Indicates in In the middle, vehicles They were not assigned to participate in content distribution.

[0071] As a further optimization of this invention, step S2.4, obtaining the maximum node transfer value within the cluster, is determined using the following method:

[0072] cluster Maximum node transfer value The maximum value is obtained by traversing within the constraints.

[0073] As a further optimization of the present invention, the optimal clustering in step S3 is determined by the following method:

[0074] 1) Before the game begins, each car is a cluster head, forming a cluster with only one node. The vehicle ID is used as the cluster ID to form the initial cluster set. This serves as the initial cluster for the game; cluster , This indicates that before the first round of the game begins, vehicle V... m A cluster with a cluster head, containing only one node V. m Where 1≤m≤N, the set of cluster head nodes is... =V;

[0075] 2) At the start of the t-th round of the game, with vehicle V... m ∈ Clusters with cluster heads , ∈ Calculate the optimal content distribution scheme within the cluster based on S2.3. And update the set of vehicle nodes that were not scheduled for content delivery in the optimal content distribution scheme. For all nodes ∈ Calculate the transfer value and find the node corresponding to the maximum transfer value. ;

[0076] 3) Each round of the game proceeds in a random order, with the cluster's turn being determined by the others. When starting the node transfer, if | |>0 and the calculated maximum node transition value ≥0, then cluster Transfer the most valuable solution To the target cluster ∈ In, and update the cluster and ,in , ;

[0077] 4) If the node is transferred =V m ,but , ;

[0078] 5) Update the game round number t=t+1, if a certain cluster exists. ∈ For the set of nodes Calculate the maximum node transfer value If ≥0, return to step 2); otherwise, proceed to step 6).

[0079] 6) If for each cluster All satisfy If the value is less than 0, then a Nash equilibrium is reached, and the final number of game rounds is T. At this point, the set of clusters... This is the optimal clustering scheme we are looking for. Attached Figure Description

[0080] Figure 1 This is a flowchart illustrating a specific implementation of the content distribution method based on an incentive mechanism in the blind spot of a highway connected vehicle network according to the present invention.

[0081] Figure 2 This is a flowchart of the process for calculating the maximum transfer value of nodes within a cluster in this invention;

[0082] Figure 3 This is a flowchart of the alliance game based on the incentive mechanism in this embodiment;

[0083] Figure 4 This is a comparison chart of the average download latency of vehicles using different methods under different blind zone lengths in this embodiment;

[0084] Figure 5 This is a comparison chart of the download incomplete rate of different methods under different blind zone lengths in this embodiment;

[0085] Figure 6 This is a comparison chart of the average download latency of vehicles using different methods under different numbers of vehicles per second in this embodiment;

[0086] Figure 7 This is a comparison chart of the download incomplete rate of different methods under different numbers of vehicles per second in this embodiment; Detailed Implementation

[0087] The specific embodiments of the present invention will now be described with reference to the accompanying drawings to enable those skilled in the art to better understand the invention. It should be particularly noted that in the following description, detailed descriptions of known functions and designs that might obscure the main content of the invention will be omitted here.

[0088] Example

[0089] Taking a 4300-meter-long two-way highway as an example, there are 6 RSUs on the road, with an 800-meter communication range interval (blind zone length) between adjacent RSUs, and service areas on both sides of the road. Vehicles can communicate within the service area base stations and RSU ranges using frequency division multiplexing to obtain partial content blocks. On average, one vehicle enters the road segment per second at a constant speed, corresponding to highway speed standards of 21 m / s, 28 m / s, or 32 m / s. The vehicle communication range radius is 200 meters, and the transmission rate is constant at 10 Mb / s. There are 20 content blocks on the road segment. The requests from vehicles are within the range of given content blocks. Each content block is 100 Mb in size and is divided into 5 equal content blocks. Vehicles in the same lane request content blocks accounting for two-thirds of the total content. Each vehicle requests one content block when entering the road segment, and the request probability follows a zipf distribution with γ=1.38. This embodiment simulates highway road conditions for 5 hours.

[0090] Figure 1 This is a flowchart illustrating a specific implementation of the content distribution method based on an incentive mechanism in the blind spot of a highway connected vehicle network according to the present invention. Figure 1 As shown, the specific implementation steps of the content distribution method based on the incentive mechanism in the blind spot of the vehicle-to-everything (V2X) highway according to the present invention include:

[0091] S1: Calculate the set of transferable vehicles for each vehicle within the blind zone:

[0092] The current collection of all vehicles in the blind spot of the connected vehicle highway is as follows N is the total number of vehicles in the blind spot, V i For the vehicle with ID i in the blind spot; V for each vehicle i V broadcasts its own directional speed, v, to nearby vehicles. i Location pos i Request content r i The set of content blocks owned is A i ={D i C i}, and its own contribution level c (i) Information; of which, D i For vehicle V i The set of requested content blocks that have been downloaded, C i This is a cached collection of content blocks not requested by the vehicle itself; after exchanging relevant information, vehicle V... i For other vehicles within the communication range V j ∈V computational communication duration :

[0093]

[0094] Where R represents the vehicle's communication range, determined based on the signal-to-noise ratio threshold of the vehicle's received signal; for each piece of content, it is divided into content blocks of equal size for transmission, with each content block having a size of M. b Vehicle V i By calculation, it can be determined whether it is related to other vehicles V. j V's communication duration Does it meet the following conditions:

[0095]

[0096] If the condition is met, it means that vehicle V i With vehicle V j The communication time is sufficient to reliably transmit a content block; among which, Indicates vehicle V i With V j The transmission rate of communication; This is a time margin parameter set to prevent transmission failure due to channel instability or excessive computation time. It is determined based on the time taken for the simulated or experimental vehicle to finally form a cluster; for vehicle V i The set of vehicles that satisfy the communication duration condition is called Near. i .

[0097] S2: Calculate the maximum node transition value within the cluster at round t based on the incentive factor:

[0098] Figure 2 This is a flowchart illustrating the calculation of the maximum transfer value of nodes within a cluster in this invention. For example... Figure 2 As shown, the specific steps for calculating the maximum transition value of nodes within a cluster include:

[0099] S2.1: Calculate the efficiency of content transfer between nodes within a cluster:

[0100] Before the start of the t-th round of the coalition game, the set of clusters is: For any cluster ,vehicle Cluster head, number of cluster members ,in, Represents the set of cluster head nodes. Represents a set The number of elements in the cluster; for any vehicle V within the cluster i If from other vehicles within the cluster Obtain a content block at [location]. This behavior is recorded as Then the receiving vehicle V i and the sending vehicle V j The content transfer benefits brought to the cluster are as follows: and The calculation is as follows:

[0101]

[0102]

[0103] in, Indicates in transmission behavior In the middle, the receiving vehicle V i Is the retrieved content block x the desired content block? , indicating vehicle V i Able to obtain the required content block, This indicates that vehicle V i Unable to obtain the required content block; Indicates in transmission behavior In the middle, the sending vehicle V jIs it possible to distribute content blocks to other vehicles? This indicates that other vehicles are able to access V. j Download or cache content block x, Indicates vehicle V j Cannot provide content blocks to other vehicles; coefficient a i and b j This is an incentive factor designed to encourage vehicles to spontaneously participate in the distribution process; the calculation method is as follows:

[0104]

[0105]

[0106] Among them, c (i) c (j) and c (k) These represent vehicle V. i V j V k The contribution score is the sum of the historical number of times a vehicle performs distribution actions within the highway blind spot. Distribution actions include caching non-requested content blocks and providing content blocks to other vehicles; V i V j V k All belong to And V i Not equal to V j ; It is a smoothing factor, and its value range is... Vehicle V i The greater the contribution, the higher the coefficient a. i The larger the value, the greater the content transfer benefit that the vehicle receives from the cluster of its requested content blocks; Vehicle V j The smaller the contribution, the lower the value of b j The larger the value, the greater the content transfer benefit that the vehicle brings to the cluster by providing content blocks to other vehicles;

[0107] S2.2: Calculate the content distribution preference for each vehicle within the cluster:

[0108] Calculate vehicle V i From other vehicles within the cluster Download a content block Maximum content delivery efficiency :

[0109]

[0110] in, It is vehicle V j The existing set of content blocks; since the vehicle cannot download new content blocks from itself, therefore If vehicle Vj Not in V i Near the set of transferable vehicles i middle, For vehicle V i Its content distribution trend i The difference between the average benefit of a vehicle as a receiver and the average benefit of a vehicle as a sender is calculated as follows:

[0111]

[0112] in, The cluster represents the cluster at the start of the t-th round of the game. Number of vehicles in China;

[0113] S2.3: Calculate the optimal content distribution scheme and maximum content delivery efficiency within each cluster:

[0114] cluster Inside The vehicle nodes are sorted from largest to smallest according to their distribution preference and assigned a cluster number: , For sorted clusters Vehicle numbered i; create a matrix H* that stores the maximum content transfer efficiency between vehicles, where the element in the i-th row and j-th element is... Indicates vehicle With vehicles To maximize the efficiency of content transmission, the calculation method for the elements in the matrix is ​​as follows:

[0115]

[0116] in, , Representing vehicles from Download a content block and a vehicle from The maximum content transfer benefit that downloading a content block brings to a cluster is calculated by S2.2; cluster The set of all possible distribution schemes is represented as Among them, the scheme { },in, Indicates vehicle and Content blocks are distributed between them. Number of connections | | Satisfies constraints That is, the number of connections must not exceed half the number of vehicles within the cluster; among which Indicates to / 2 rounds down; any connection Benefits Let be the element value corresponding to the i-th row and j-th column of matrix H*;

[0117] Regarding the plan Total efficiency of intra-cluster content transmission The sum of the benefits of all connections within the cluster is calculated as follows:

[0118]

[0119] For clusters Selection of the optimal content distribution scheme within the cluster, and the overall efficiency of optimal content delivery within the cluster. For a set of distribution schemes The objective function for calculating the maximum content transfer efficiency within a cluster is: (This is the sum of the benefits of all possible solutions.)

[0120]

[0121]

[0122] Among them, constraint (1) Representation scheme China Vehicle Whether or not they are assigned to participate in content distribution Representation scheme China Vehicle Not assigned to participate in content distribution Representation scheme China Vehicle The content is distributed to other vehicles; constraint (2) indicates that the number of connections in each scheme does not exceed the total number of vehicles in the cluster. Half of; constraint (3) indicates that the benefit of the content transferred between the two vehicles is greater than 0; constraint (4) indicates that the benefit of the content transferred between the two vehicles is greater than 0. Vehicles that transmit content Must be in the vehicle In the set of transferable vehicles, Cluster Vehicle with internal number i A collection of transferable vehicles;

[0123] Computational clusters The optimal intra-cluster distribution scheme is The maximum transmission efficiency is The set of vehicles not scheduled to participate in optimal cluster content transmission is , The calculation method is as follows:

[0124] The method for selecting the optimal intra-cluster distribution scheme for each cluster is as follows: in matrix H*, find any element greater than 0. , then set all elements in the i-th row, the i-th column, the j-th row, and the j-th column to zero, and then find the next element greater than zero , until all elements are set to zero, such that the sum of the selected elements sum is maximized, which is the maximum transmission benefit; the set of corresponding connections corresponding to the selected elements at this time is the optimal intra-cluster distribution scheme ;

[0125] The selection process is as follows:

[0126] 1) Use a greedy search algorithm to find a local optimal solution for matrix H* and incorporate it into the solution set ;

[0127] 2) Set the solution sequence number k=2;

[0128] 3) Set the row number i=1;

[0129] 4) Set the column number j= ;

[0130] 5) Under the condition of satisfying the constraint of calculating maximum transmission benefit, for each solution in the solution set , replace the vehicle that performs content transmission with vehicle with vehicle , retain all connections in the solution that include vehicles satisfying lb<i , where lb is the sequence number of vehicle after arrangement in the cluster , and obtain remaining connections through greedy search; the collection of these connections is the new solution ;

[0131] 6) If the set , perform step 7); otherwise, perform step 8);

[0132] 7) k=k+1, and incorporate the new solution into the solution set ;

[0133] 8) j=j+1, if j< , return to step 5); otherwise, perform step 9);

[0134] 9) i=i+1, if i< , return to step 4); otherwise, perform step 10);

[0135] 10) Calculate the total benefit for each solution in the solution set , and the solution with the maximum total benefit is the optimal intra-cluster content distribution scheme for cluster ​ The corresponding total benefits That is, a cluster Maximum content transfer efficiency within the cluster;

[0136] Optimal intra-cluster distribution scheme In this context, the set of vehicles not scheduled to participate in optimal intra-cluster content transmission is: , , The calculation is as follows:

[0137]

[0138] in, Indicates in In the middle, vehicles They were not assigned to participate in content distribution.

[0139] S2.4: Calculate the maximum intra-cluster node transition value for each cluster:

[0140] For clusters According to the optimal content distribution scheme sought in S2.3 The set of vehicles not scheduled to participate in optimal cluster content transmission is Calculate vehicle nodes The transfer value is calculated as follows:

[0141] When vehicle node From cluster Transfer to vehicles Clusters with cluster heads Then, a new cluster is formed. , Then the value of that node is transferred. for:

[0142]

[0143] in, To increase the benefits brought about by transferring this node, and These are the newly formed clusters and Maximum content delivery efficiency and They are clusters and The maximum content delivery efficiency; It is the cost of moving that node, determined by the game round number t and the target node. Current number of members | Decision It is a cost coefficient;

[0144] Computational clusters Maximum node transfer value within the cluster The method is as follows:

[0145]

[0146] Satisfy the maximum transfer value The corresponding node is , ;cluster Maximum node transfer value The maximum value is obtained by traversing within the constraints.

[0147] S3: Calculate the optimal clustering method and optimal intra-cluster content distribution scheme based on the incentive mechanism:

[0148] Figure 3 This is a flowchart of the alliance game based on the incentive mechanism in this embodiment. Figure 3 As shown, the specific steps for obtaining the optimal clustering method and the optimal content distribution scheme within a cluster based on the incentive mechanism include:

[0149] 1) Before the game begins, each car is a cluster head, forming a cluster with only one node. The vehicle ID is used as the cluster ID to form the initial cluster set. This serves as the initial cluster for the game; cluster , This indicates that before the first round of the game begins, vehicle V... m A cluster with a cluster head, containing only one node V. m Where 1≤m≤N, the set of cluster head nodes is... =V;

[0150] 2) At the start of the t-th round of the game, with vehicle V... m ∈ Clusters with cluster heads , ∈ Calculate the optimal content distribution scheme within the cluster based on S2.3. And update the set of vehicle nodes that were not scheduled for content delivery in the optimal content distribution scheme. For all nodes ∈ Calculate the transfer value and find the node corresponding to the maximum transfer value. ;

[0151] 3) Each round of the game proceeds in a random order, with the cluster's turn being determined by the others. When starting the node transfer, if | |>0 and the calculated maximum node transition value ≥0, then cluster Transfer the most valuable solution To the target cluster ∈ In, and update the cluster and ,in , ;

[0152] 4) If the node is transferred =V m ,but , ;

[0153] 5) Update the game round number t=t+1, if a certain cluster exists. ∈ For the set of nodes Calculate the maximum node transfer value If ≥0, return to step 2); otherwise, proceed to step 6).

[0154] 6) If for each cluster All satisfy If the value is less than 0, then a Nash equilibrium is reached, and the final number of game rounds is T. At this point, the set of clusters... This is the optimal clustering scheme we are looking for.

[0155] S4: Transfer content blocks and update contribution using the optimal intra-cluster content distribution scheme:

[0156] After obtaining the optimal clustering method and the optimal intra-cluster content distribution scheme based on the method in S3, the cluster head node of each cluster arranges content transmission between intra-cluster nodes through broadcasting. After the transmission is completed, the transmission results of vehicles within the cluster are collected, and the vehicle contribution is updated according to the results.

[0157] For any cluster in the final clustering Optimal distribution scheme within the cluster In the middle, vehicles , From another vehicle Download content x here, x A m,j , where A m,j It is a vehicle If the set of content blocks already owned is given, then this behavior is denoted as If the content block is successfully transmitted, the cluster head vehicle updates the vehicle. Contribution c (m,i) and vehicles Contribution c (m,j) The update method is as follows:

[0158]

[0159]

[0160] That is, if the receiving vehicle If a receiving vehicle caches a content block that is not part of its own request, its contribution increases; if the sending vehicle... If content is provided, the sender's vehicle contribution increases.

[0161] To verify the effectiveness and practicality of the present invention, an ablation comparison method was designed in a specific embodiment, the specific method of which is as follows:

[0162] Method 1: No-cooperation method: A vehicle on the road randomly selects a nearby vehicle and randomly distributes a content block to it;

[0163] Method 2: One-time clustering method: Based on the optimal content distribution scheme within a cluster, vehicles are clustered once according to proximity, location, and speed. Once a cluster is formed, it does not change until the end of the distribution. Each cluster is assigned content by the cluster head according to the optimal content distribution scheme calculated by S3 in this embodiment.

[0164] Method 3: Coalition Game Theory: Based on maximizing the number of content blocks, vehicles form alliances by maximizing the number of content blocks within the alliance, and request content blocks from nearby vehicles in a random order within the alliance.

[0165] The following technical indicators were used to measure the performance of the method:

[0166] 1) Average download latency per vehicle: The average time taken for a vehicle to complete the download before leaving the blind spot of the road;

[0167] 2) Download incomplete rate: The percentage of vehicles that did not obtain the required content when leaving the blind spot of the road out of the total number of vehicles leaving the road.

[0168] To better illustrate the technical effects of the present invention, multiple sets of comparative experiments were conducted by changing the length of blind spots in road sections and the number of vehicles per second on the road. Figure 4 This is a comparison chart of the average download latency of vehicles using different methods under different blind zone lengths in this embodiment. Figure 5 This is a comparison chart of the download incompleteness rate of different methods under different blind zone lengths in this embodiment. For example... Figure 4 and Figure 5 As shown, with the increase in blind spot length, the RSU becomes sparser, making it more difficult for vehicles to obtain the requested content block from the RSU, resulting in a significant increase in download latency. However, due to the increase in road length, the download incompleteness rate is reduced. Compared with other methods, the method of this invention has the lowest download latency and the lowest download incompleteness rate in the scenario of sparse RSU.

[0169] Figure 6 This is a comparison chart of the average download latency of vehicles using different methods under different numbers of vehicles per second in this embodiment. Figure 7 This is a comparison chart of the download incompleteness rate of different methods under different numbers of vehicles arriving per second in this embodiment. For example... Figure 6 and Figure 7 As shown, with the increase in the number of vehicles arriving per second, the vehicle density on the road increases. Each vehicle within the communication range has more options to choose from for content block transmission, and the content block density also increases. Vehicles have more opportunities to obtain the content blocks they need, resulting in a significant decrease in download latency and download incompleteness rate. Compared to other methods, the method of this invention has similar performance when the average number of vehicles arriving per second is low, but exhibits significant advantages in latency and incompleteness rate when the average number of vehicles arriving per second is high.

[0170] In summary, this invention demonstrates good performance under various blind spot conditions on connected vehicle highways, exhibiting high effectiveness and adaptability. Compared to other methods, it is more suitable for conditions with sparse RSUs and a large number of oncoming vehicles, and better reflects the actual blind spot situation on connected vehicle highways.

[0171] Although the illustrative specific embodiments of the present invention have been described above to enable those skilled in the art to understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of the present invention are protected.

Claims

1. A content distribution method based on an incentive mechanism in the blind spot of a vehicle-to-everything (V2X) highway, characterized in that, Includes the following steps: S1: Calculate the set of transferable vehicles for each vehicle within the blind zone: The current collection of all vehicles in the blind spot of the connected vehicle highway is as follows N is the total number of vehicles in the blind spot, V i For the vehicle with ID i in the blind spot; V for each vehicle in the blind spot i V, exchanges information with nearby vehicles and calculates the set of transmissible vehicles Near. i And broadcast Near i ; S2: Calculate the maximum node transition value within the cluster at round t based on the incentive factor: S2.1: Calculate the efficiency of content transfer between nodes within a cluster: Before the start of the t-th round of the coalition game, the set of clusters is: For any cluster ,vehicle Cluster head, number of cluster members ,in, Represents the set of cluster head nodes. Represents a set The number of elements in the cluster; for any vehicle V within the cluster i If from other vehicles within the cluster Obtain a content block at [location]. This behavior is recorded as Then the receiving vehicle V i and the sending vehicle V j The content transfer benefits brought to the cluster are as follows: and The calculation is as follows: in, Indicates in transmission behavior In the middle, the receiving vehicle V i Is the retrieved content block x the desired content block? , indicating vehicle V i Able to obtain the required content block, This indicates that vehicle V i Unable to obtain the required content block; Indicates in transmission behavior In the middle, the sending vehicle V j Is it possible to distribute content blocks to other vehicles? This indicates that other vehicles are able to access V. j Download or cache content block x, Indicates vehicle V j Cannot provide content blocks to other vehicles; coefficient a i and b j This is an incentive factor designed to encourage vehicles to spontaneously participate in the distribution process; the calculation method is as follows: Among them, c (i) c (j) and c (k) These represent vehicle V. i V j V k The contribution score is the sum of the historical number of times a vehicle performs distribution actions within the highway blind spot. Distribution actions include caching non-requested content blocks and providing content blocks to other vehicles; V i V j V k All belong to And V i Not equal to V j ; It is a smoothing factor; S2.2: Calculate the content distribution preference for each vehicle within the cluster: Calculate vehicle V i From other vehicles within the cluster Download a content block Maximum content delivery efficiency : in, It is vehicle V j The existing set of content blocks; since the vehicle cannot download new content blocks from itself, therefore If vehicle V j Not in V i Near the set of transferable vehicles i middle, For vehicle V i Its content distribution trend i The difference between the average benefit of a vehicle as a receiver and the average benefit of a vehicle as a sender is calculated as follows: in, The cluster represents the cluster at the start of the t-th round of the game. Number of vehicles in China; S2.3: Calculate the optimal content distribution scheme and maximum content delivery efficiency within each cluster: cluster Inside The vehicle nodes are sorted from largest to smallest according to their distribution preference and assigned a cluster number: ,in, For sorted clusters Vehicle numbered i; create a matrix H* that stores the maximum content transfer efficiency between vehicles, where the element in the i-th row and j-th element is... Indicates vehicle With vehicles To maximize the efficiency of content transmission, the calculation method for the elements in the matrix is ​​as follows: in, , Representing vehicles from Download a content block and a vehicle from The maximum content transfer benefit that downloading a content block brings to a cluster is calculated by S2.2; cluster The set of all possible distribution schemes is represented as Among them, the scheme { }, Indicates vehicle and Content blocks are distributed between them. Number of connections | | Satisfies constraints That is, the number of connections must not exceed half the number of vehicles within the cluster; among which Indicates to / 2 rounds down; any connection Benefits Let be the element value corresponding to the i-th row and j-th column of matrix H*; Regarding the plan Total efficiency of intra-cluster content transmission The sum of the benefits of all connections within the cluster is calculated as follows: For clusters Selection of the optimal content distribution scheme within the cluster, and the overall efficiency of optimal content delivery within the cluster. For a set of distribution schemes The objective function for calculating the maximum content transfer efficiency within a cluster is: (This is the sum of the benefits of all possible solutions.) Among them, constraint (1) Representation scheme China Vehicle Whether or not they are assigned to participate in content distribution Representation scheme China Vehicle Not assigned to participate in content distribution Representation scheme China Vehicle The content is distributed to other vehicles; constraint (2) indicates that the number of connections in each scheme does not exceed the total number of vehicles in the cluster. Half of; constraint (3) indicates that the benefit of the content transferred between the two vehicles is greater than 0; constraint (4) indicates that the benefit of the content transferred between the two vehicles is greater than 0. Vehicles that transmit content Must be in the vehicle In the set of transferable vehicles, Cluster Vehicle with internal number i A collection of transferable vehicles; Calculate and obtain clusters The optimal intra-cluster distribution scheme is The maximum transmission efficiency is The set of vehicles not scheduled to participate in optimal cluster content transmission is , ; S2.4: Calculate the maximum intra-cluster node transition value for each cluster: For clusters According to the optimal content distribution scheme sought in S2.3 The set of vehicles not scheduled to participate in optimal cluster content transmission is Calculate vehicle nodes The transfer value is calculated as follows: When vehicle node From cluster Transfer to vehicles Clusters with cluster heads Then, a new cluster is formed. , Then the value of that node is transferred. for: in, To increase the benefits brought about by transferring this node, and These are the newly formed clusters and Maximum content delivery efficiency and They are clusters and The maximum content delivery efficiency; It is the cost of moving that node, determined by the game round number t and the target node. Current number of members | Decision It is a cost coefficient; Computational clusters Maximum node transfer value within the cluster The method is as follows: Satisfy the maximum transfer value The corresponding node is , ; S3: Calculate the optimal clustering method and optimal intra-cluster content distribution scheme based on the incentive mechanism: Based on the initial cluster set The optimal clustering method is obtained by conducting a coalition game and calculating the maximum node transition value within a cluster based on S2.4, until the maximum node transition value within all clusters is less than zero. T represents the number of rounds of coalition game played to reach Nash equilibrium; the cluster head node of each cluster calculates and obtains the optimal content distribution scheme within the cluster based on the method in S2.3; S4: Transfer content blocks and update contribution using the optimal intra-cluster content distribution scheme: After obtaining the optimal clustering method and the optimal intra-cluster content distribution scheme based on the method in S3, the cluster head node of each cluster arranges content transmission between intra-cluster nodes through broadcasting. After the transmission is completed, the transmission results of vehicles within the cluster are collected, and the vehicle contribution is updated according to the results. For any cluster in the final clustering Optimal distribution scheme within the cluster In the middle, vehicles , From another vehicle Download content x here, x A m,j , where A m,j It is a vehicle If the set of content blocks already owned is given, then this behavior is denoted as If the content block is successfully transmitted, the cluster head vehicle updates the vehicle. Contribution c (m,i) and vehicles Contribution c (m,j) The update method is as follows: 。 2. The content distribution method based on an incentive mechanism in the blind spot of a vehicle-to-everything (V2X) highway according to claim 1, characterized in that, The set of transportable vehicles is determined in step S1 using the following method: Each vehicle V i V broadcasts its own directional speed, v, to nearby vehicles. i Location pos i Request content r i The set of content blocks owned is A i ={D i C i }, and its own contribution level c (i) Information; of which, D i For vehicle V i The set of requested content blocks that have been downloaded, C i This is a cached collection of content blocks not requested by the vehicle itself; after exchanging relevant information, vehicle V... i For other vehicles within the communication range V j ∈V computational communication duration : Where R represents the vehicle's communication range, determined based on the signal-to-noise ratio threshold of the vehicle's received signal; for each piece of content, it is divided into content blocks of equal size for transmission, with each content block having a size of M. b Vehicle V i By calculation, it can be determined whether it is related to other vehicles V. j V's communication duration Does it meet the following conditions: If the condition is met, it means that vehicle V i With vehicle V j The communication time is sufficient to reliably transmit a content block; among which, Indicates vehicle V i With V j The transmission rate of communication; This is a time margin parameter set to prevent transmission failure due to channel instability or excessive computation time. It is determined based on the time taken for the simulated or experimental vehicle to finally form a cluster; for vehicle V i The set of vehicles that satisfy the communication duration condition is called Near. i .

3. The content distribution method based on an incentive mechanism in the blind spot of a vehicle-to-everything (V2X) highway according to claim 1, characterized in that, The optimal distribution scheme within the cluster in step S2.3 is determined using the following method: The method for selecting the optimal intra-cluster distribution scheme for each cluster is as follows: in matrix H*, find any element greater than 0. Then set all elements in row i, column i, row j, and column j to zero, and then search for the next element greater than 0. Continue until all elements are set to zero, so that the selected element... sum maximum, To achieve maximum transmission efficiency, the set of connections corresponding to the selected multiple elements represents the optimal intra-cluster distribution scheme. ; The selection process is as follows: 1) Use a greedy search algorithm to find a local optimum for matrix H*. , incorporated into the scheme set middle; 2) Let the scheme number k=2; 3) Let line number i = 1; 4) Let the number of columns j = ; 5) Under the condition of satisfying the constraint of calculating the maximum transmission benefit, for the solution set in each solution, replace the vehicle that performs content transmission with vehicle by vehicle , retain all connections in the solution that include vehicles satisfying lb<i , where lb is the serial number of vehicle in the cluster after arrangement, and obtain the remaining connections through greedy search, and the set of these connections is the new solution ; 6) If set If yes, proceed to step 7); otherwise, proceed to step 8). 7) k = k + 1, and the new scheme Incorporation scheme set middle; 8) j = j + 1, if j < (Return to step 5); otherwise, proceed to step 9). 9) i=i+1, if i< (Return to step 4); otherwise execute step 10). 10) For the set of solutions For each scheme, calculate the total benefit; the scheme with the largest total benefit is the cluster. Optimal content distribution scheme within the cluster The corresponding total benefits That is, a cluster Maximum content transfer efficiency within the cluster; Optimal intra-cluster distribution scheme In this context, the set of vehicles not scheduled to participate in optimal intra-cluster content transmission is: , , The calculation is as follows: in, Indicates in In the middle, vehicles They were not assigned to participate in content distribution.

4. The content distribution method based on an incentive mechanism in the blind spot of a vehicle-to-everything (V2X) highway according to claim 1, characterized in that, The maximum node transfer value within the cluster obtained in step S2.4 is determined using the following method: cluster Maximum node transfer value The maximum value is obtained by traversing within the constraints.

5. A content distribution method based on an incentive mechanism in the blind spot of a vehicle-to-everything (V2X) highway according to claim 1, characterized in that, The optimal clustering in step S3 is determined using the following method: 1) Before the game begins, each car is a cluster head, forming a cluster with only one node. The vehicle ID is used as the cluster ID to form the initial cluster set. This serves as the initial cluster for the game; cluster , This indicates that before the first round of the game begins, vehicle V... m A cluster with a cluster head, containing only one node V. m Where 1≤m≤N, the set of cluster head nodes is... =V; 2) At the start of the t-th round of the game, with vehicle V... m ∈ Clusters with cluster heads , ∈ Calculate the optimal content distribution scheme within the cluster based on S2.

3. And update the set of vehicle nodes that were not scheduled for content delivery in the optimal content distribution scheme. For all nodes ∈ Calculate the transfer value and find the node corresponding to the maximum transfer value. ; 3) Each round of the game proceeds in a random order, with the cluster's turn being determined by the others. When starting the node transfer, if | |>0 and the calculated maximum node transition value ≥0, then cluster Transfer the most valuable solution To the target cluster ∈ In, and update the cluster and ,in , ; 4) If the node is transferred =V m ,but , ; 5) Update the game round number t=t+1, if a certain cluster exists. ∈ For the set of nodes Calculate the maximum node transfer value If ≥0, then return to step 2); Otherwise, proceed to step 6). 6) If for each cluster All satisfy If the value is less than 0, then a Nash equilibrium is reached, and the final number of game rounds is T. At this point, the set of clusters... This is the optimal clustering scheme we are looking for.

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