A method, system, device and medium for allocating collaborative resources in an internet of vehicles

Abstract

The present invention discloses a method, system, device and medium for allocating collaborative resources in an Internet of Vehicles, comprising: taking the maximum roadside base station revenue as an objective function, constructing an alliance structure between base stations; wherein the alliance structure between base stations includes a plurality of base station alliances; determining the content to be stored in each base station alliance in the alliance structure between base stations, and obtaining an alliance cache decision result; splitting and updating the base station alliances whose resource utilization is lower than a preset threshold, and updating the cache decision result; dividing each content to be requested, and according to the updated cache decision result, storing a plurality of content blocks of the same size in a plurality of base station alliances in the updated alliance structure between base stations, thus obtaining an Internet of Vehicles collaborative resource allocation result; the present invention meets the Internet of Vehicles edge cache scenario of high-speed vehicle operation, improves cache efficiency, ensures data transmission and service quality, reduces the delay in user acquisition of content and effectively improves the user experience of terminal users.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Vehicles edge cache technology, and in particular relates to an Internet of Vehicles collaborative resource allocation method, system, device and medium. Background Art

[0002] In intelligent road transportation, the Internet of Vehicles system integrates network information between vehicles, road infrastructure and users. It can provide a variety of on-board applications and improve the safety and comfort of road traffic through the vehicle Internet network. Edge caching is a technology that pre-caches content on edge nodes and deploys data by utilizing the user proximity of edge nodes, which can effectively solve the problems caused by massive data growth. Users make requests from the edge of the network close to them, which reduces content request latency and provides a better user experience. Caching content on edge nodes reduces data transmission in the return link and can reduce the energy consumption of macro base stations sending data. When multiple users request the same content, edge caching can make full use of multicast transmission cache files and use network information collected in edge cache servers, such as user preferences, content popularity, mobility information, user social information, etc. to more accurately analyze user behavior patterns and improve cache benefits.

[0003] At present, in the existing Internet of Vehicles edge computing network environment, V2I communication is mostly used to provide connections between end-user vehicles and roadside units (RSUs), and by caching content in the roadside units (RSUs), low-latency content transmission is provided to end-user vehicles. However, in road scenarios, high-speed moving vehicles often pass through multiple roadside units (RSUs) when transmitting content. For some files with large storage volumes, it is impossible to obtain all content from a single edge cache node. At the same time, due to the time-varying communication conditions caused by the high-speed movement of vehicles, the request latency is high and the transmission efficiency is reduced, which seriously affects the user experience. Summary of the invention

[0004] In response to the technical problems existing in the prior art, the present invention provides a method, system, device and medium for collaborative resource allocation in an Internet of Vehicles (IoV) to solve the technical problems that in the existing IoV edge computing network environment, high-speed moving vehicles cannot obtain all content from a single edge cache node; and due to the time-varying communication conditions caused by the high-speed movement of vehicles, the request delay is high and the transmission efficiency is reduced.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] The present invention provides a method for allocating collaborative resources in an Internet of Vehicles (IoV) edge computing network, which is used in a collaborative resource allocation process in an IoV edge computing network; wherein the end-edge-cloud collaborative architecture of the IoV edge computing network includes a remote cloud, a plurality of roadside base stations, and a plurality of end-user vehicles; the remote cloud, the plurality of roadside base stations, and the plurality of end-user vehicles are interconnected by wireless communication;

[0007] The Internet of Vehicles collaborative resource allocation method includes:

[0008] Step 1: According to the cacheable content, storage capacity and transmission volume between the roadside base stations and the terminal user vehicle, an alliance structure between base stations is constructed with the maximum roadside base station revenue as the objective function; wherein the alliance structure between base stations includes a plurality of base station alliances;

[0009] Step 2: Perform cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result;

[0010] Step 3: According to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance whose resource utilization is lower than a preset threshold, so as to obtain an updated alliance structure between the base stations;

[0011] Step 4: Repeat steps 1-3 until the alliance structure between the updated base stations does not change any more;

[0012] Step 5: Repeat the operation of step 2 to determine the content to be stored by each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result;

[0013] Step 6: Divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, store the number of content blocks of the same size in a number of base station alliances in the updated alliance structure between base stations, so as to obtain the Internet of Vehicles collaborative resource allocation result.

[0014] Furthermore, in step 1, the objective function is:

[0015] P:maxv(x)=u(x)-csot(x)

[0016]

[0017]

[0018]

[0019]

[0020] Among them, maxv(x) is the optimization goal, that is, maximizing the revenue of the roadside base station; u(x) is the total revenue obtained by the roadside base station; csot(x) is the total cost of the roadside base station; is the number of content blocks planned to be stored in the jth roadside base station; C1 is constraint 1, i.e., the storage capacity limit of the roadside base station; L is the content block size; B j is the storage capacity of the jth roadside base station; c e is the content to be requested with sequence number e; C2 is constraint 2, i.e., the maximum transmission volume between the roadside base station and the terminal user vehicle; B ij is the maximum transmission volume between the jth roadside base station and the i-th end-user vehicle; β j Indicates whether the end-user vehicle can obtain the complete content block, with a value of 1 or 0; Request download content for end-user vehicles c i The cost of; ε is the coefficient that converts transmission energy consumption into overhead; is the transmission power of the roadside base station; t i,j is the transmission time between the jth roadside base station and the i-th end-user vehicle.

[0021] Furthermore, in step 1, according to the cacheable content, storage capacity and transmission volume between the roadside base stations and the terminal user vehicle, a collaborative matching algorithm is adopted to build an alliance structure between the base stations with the maximum roadside base station revenue as the objective function;

[0022] The alliance structure between the base stations is:

[0023] Π={S r1 ,S r2 ,…,S rm}

[0024] Among them, Π is the alliance structure between base stations; S rm is the mth base station alliance;

[0025] The construction process of each base station alliance is as follows:

[0026] According to the cacheable content, storage capacity and transmission volume between the roadside base station and the terminal user vehicle, a matching factor of each roadside base station is set; and roadside base stations with similar matching factors are grouped as a base station alliance;

[0027] Among them, the matching factor of the i-th roadside base station is:

[0028]

[0029] Among them, δ iis the matching factor of the i-th roadside base station; λ is the parameter factor; is the storage capacity of the i-th roadside base station; B i is the transmission volume between the i-th roadside base station and the passing end-user vehicle.

[0030] Furthermore, in step 2, a cache decision is made according to a preset content placement algorithm to determine the content to be stored in each base station alliance in the alliance structure between the base stations, and in the process of obtaining the alliance cache decision result, the preset content placement algorithm is a greedy algorithm;

[0031] The specific process is as follows:

[0032] Get the total storage capacity R(S) of each base station alliance in the alliance structure between the base station alliances i ) and the total transmission volume B(S i );

[0033] Calculate the revenue of each content to be requested, and sort all the content to be requested according to the revenue of each content to be requested to obtain a content revenue sorting result;

[0034] According to the content revenue ranking result, according to the total storage space R (S i ) and the total transmission volume B(S i ), all the content to be requested is stored in the base station alliance with the closest storage capacity and transmission capacity, and the alliance cache decision result is obtained; wherein the alliance cache decision result includes the base station alliance cache decision vector and the roadside base station cache decision vector.

[0035] Furthermore, in step 3, according to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance with low resource utilization and a preset threshold, and the process of obtaining the updated alliance structure between the base stations is as follows:

[0036] Calculating a resource balancing factor of each roadside base station according to the alliance cache decision result;

[0037] The resource balancing factor of each roadside base station is compared with the preset resource utilization threshold. If the resource balancing factor of a roadside base station is less than the preset resource utilization threshold, the roadside base station is removed from the corresponding base station alliance to obtain an updated alliance structure between base stations.

[0038] Furthermore, the resource balancing factor of each roadside base station is:

[0039] ε j =(B1)+(1-α)(2)

[0040] B1=max(x k L) / j

[0041]

[0042] Among them, ε j is the resource balancing factor of the jth roadside base station; B1 is the ratio of the content storage capacity to the transmission capacity in the roadside base station; B2 is the total storage capacity utilization rate of the roadside base station; x k is the number of content blocks stored in the jth base station.

[0043] Furthermore, the process of dividing each content to be requested to obtain a number of content blocks of the same size is as follows:

[0044] By using the fountain coding method, each content to be requested is divided into a number of content blocks of the same size, that is, a number of content blocks of the same size are obtained.

[0045] The present invention also provides a vehicle network collaborative resource allocation system, which is used in the collaborative resource allocation process in the vehicle network edge computing network; wherein the terminal-edge-cloud collaborative architecture of the vehicle network edge computing network includes a remote cloud, a plurality of roadside base stations and a plurality of terminal user vehicles; the remote cloud, the plurality of roadside base stations and the plurality of terminal user vehicles are interconnected by wireless communication;

[0046] The Internet of Vehicles collaborative resource allocation system includes:

[0047] An alliance building module is used to build an alliance structure between base stations based on the cacheable content, storage capacity and transmission volume between the end-user vehicles of the roadside base stations, taking the maximum roadside base station revenue as the objective function; wherein the alliance structure between the base stations includes a plurality of base station alliances;

[0048] A cache decision module, used to make a cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result;

[0049] An alliance updating module is used to split and update the base station alliances with low resource utilization and a preset threshold according to the alliance cache decision result and use a resource balancing method to obtain an updated alliance structure between the base stations;

[0050] A first operation repetition module, used to repeat the operations of the alliance construction module, the cache decision module and the alliance update module until the alliance structure between the updated base stations does not change any more;

[0051] A second operation repeating module, configured to repeat the operation of the cache decision module, determine the content to be stored by each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result;

[0052] The resource allocation module is used to divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, the number of content blocks of the same size are stored in a number of base station alliances in the updated alliance structure between base stations, that is, to obtain the Internet of Vehicles collaborative resource allocation result.

[0053] The present invention also provides a vehicle networking cooperative resource allocation device, comprising:

[0054] Memory for storing computer programs;

[0055] A processor is used to implement the steps of the vehicle network collaborative resource allocation method when executing the computer program.

[0056] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the vehicle network collaborative resource allocation method are implemented.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] The present invention provides a method and system for allocating collaborative resources in an Internet of Vehicles. Under the storage capacity constraint of a roadside base station and taking into account the transmission capacity limit between the roadside base station and the terminal user's vehicle, an alliance structure between base stations is constructed with the goal of maximizing the roadside base station revenue. At the same time, according to the alliance cache decision result, a resource balancing method is used to split and update the alliance structure between base stations to achieve a Pareto optimal structure. The divided content blocks are stored in the corresponding base station alliance to maximize the resource utilization and revenue of the system, meet the Internet of Vehicles edge cache scenario with high-speed vehicle operation, improve cache efficiency, ensure data transmission and service quality, reduce the delay in user acquisition of content, and effectively improve the user experience of terminal users. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a schematic diagram of the end-edge-cloud collaborative architecture of the Internet of Vehicles edge computing network in the present invention;

[0060] Figure 2 This is a flow chart of the vehicle networking collaborative resource allocation method described in the present invention. DETAILED DESCRIPTION

[0061] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail in the following specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0062] The present invention provides a method for allocating collaborative resources in an Internet of Vehicles (IoV) edge computing network; Figure 1 As shown, the end-edge-cloud coordination architecture of the Internet of Vehicles edge computing network includes a remote cloud, several roadside base stations and several end-user vehicles; the remote cloud, several roadside base stations and several end-user vehicles are interconnected by wireless communication to complete edge caching decisions and content transmission.

[0063] The following takes the collaborative resource allocation process of the Internet of Vehicles in a highway scenario as an example; wherein a base station set R consisting of several roadside base stations is defined; the e contents to be requested constitute a content set C, and the size of each content is different.

[0064] Among them, the base station set R is:

[0065] R={r1,r2,…,r j ,…,r m}

[0066] Among them, r i is the jth roadside base station, and m is the total number of roadside base stations;

[0067] Among them, the content set C is:

[0068] C={c1,c2,…,c i ,…,c e}

[0069] Among them, c i The content to be requested with sequence number i.

[0070] As attached Figure 2 As shown, the Internet of Vehicles collaborative resource allocation method specifically includes the following steps:

[0071] Step 1: Based on the cacheable content of several roadside base stations, their own storage capacity and the transmission volume between the terminal user's vehicle, a collaborative matching algorithm is adopted, with the maximum roadside base station revenue as the objective function, to build an alliance structure between base stations; wherein the alliance structure between base stations includes several base station alliances.

[0072] Wherein, the objective function is:

[0073] P:maxv(x)=u(x)-csot(x)

[0074]

[0075]

[0076]

[0077]

[0078] Among them, maxv(x) is the optimization goal, that is, maximizing the revenue of the roadside base station; u(x) is the total revenue obtained by the roadside base station; csot(x) is the total cost of the roadside base station; is the number of content blocks planned to be stored in the jth roadside base station; C1 is constraint 1, i.e., the storage capacity limit of the roadside base station; L is the content block size; B j is the storage capacity of the jth roadside base station; c e is the content to be requested with sequence number e; C2 is constraint 2, i.e., the maximum transmission volume between the roadside base station and the terminal user vehicle; B ij is the maximum transmission volume between the jth roadside base station and the i-th end-user vehicle; β j Indicates whether the end-user vehicle can obtain the complete content block, with a value of 1 or 0; Request download content for end-user vehicles c i The cost of; ε is the coefficient that converts transmission energy consumption into overhead; is the transmission power of the roadside base station; t i,j is the transmission time between the jth roadside base station and the i-th end-user vehicle.

[0079] The alliance structure between the base stations is:

[0080] Π={S r1 ,S r2 ,…,S rm}

[0081] Among them, Π is the alliance structure between base stations; S rm is the mth base station alliance.

[0082] In the present invention, a potential partner is found for each roadside base station through a collaborative matching algorithm; specifically, the roadside base stations are matched based on the storage capacity and communication transmission volume of the roadside base stations as initial conditions, and an alliance is formed by finding roadside base stations with similar matching factors, and the base station matching vectors are added as a base station alliance, so that the corresponding roadside base stations have a tendency to form an alliance, thereby obtaining an alliance structure between base stations.

[0083] Specifically, the construction process of each base station alliance is as follows:

[0084] According to the cacheable content, storage capacity and transmission volume between the roadside base station and the terminal user vehicle, a matching factor of each roadside base station is set; and roadside base stations with similar matching factors are grouped as a base station alliance;

[0085] Among them, the matching factor of the i-th roadside base station is:

[0086]

[0087] Among them, δ i is the matching factor of the i-th roadside base station, which represents the number of content types that the i-th roadside base station can store; λ is the parameter factor; is the storage capacity of the i-th roadside base station; B i is the transmission volume between the i-th roadside base station and the passing end-user vehicle.

[0088] Step 2: Perform cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result; wherein the content placement algorithm is a greedy algorithm.

[0089] In the present invention, according to the alliance structure between base stations constructed in step 1, a cache decision is made through a preset content placement algorithm to determine the content to be stored in each base station alliance; wherein, by obtaining the total storage capacity and total transmission capacity of each base station alliance, the revenue of each content to be requested is calculated and sorted according to the size of the revenue, and according to the sorting result and the total transmission capacity of each base station alliance, the content to be requested is placed in the base station alliance with the closest transmission capacity to obtain the alliance cache decision result.

[0090] Specifically, the process of obtaining the alliance cache decision result is as follows:

[0091] Get the total storage capacity R(S) of each base station alliance in the alliance structure between the base station alliances i ) and the total transmission volume B(S i );

[0092] Calculate the revenue of each content to be requested, and sort all the content to be requested according to the revenue of each content to be requested to obtain a content revenue sorting result;

[0093] According to the content revenue ranking result, according to the total storage space R (S i ) and the total transmission volume B(S i), all the content to be requested is stored in the base station alliance with the closest storage capacity and transmission capacity, and the alliance cache decision result is obtained; wherein the alliance cache decision result includes the base station alliance cache decision vector θ′ and the roadside base station cache decision vector θ.

[0094] Among them, the base station alliance cache decision vector θ′ is:

[0095]

[0096] in, The content that needs to be cached for the nth base station alliance;

[0097] The roadside base station cache decision vector θ is calculated by the ratio of the transmission volume of each roadside base station to the total transmission volume of the base station alliance; wherein the cache decision vector θ of the jth roadside base station is j for:

[0098]

[0099] in, Cache content c for the jth roadside base station i The number of content blocks.

[0100] Step 3: According to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance whose resource utilization is lower than a preset threshold, so as to obtain an updated alliance structure between the base stations.

[0101] In the present invention, based on the alliance cache decision result in step 2, alliance splitting is performed through resource balancing, that is, the base station alliance whose utilization rate is lower than the preset threshold is split and updated to obtain the updated alliance structure between the base stations.

[0102] Specifically, according to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance whose resource utilization is lower than a preset threshold, so as to obtain the updated alliance structure between the base stations, which is specifically as follows:

[0103] Calculating a resource balancing factor of each roadside base station according to the alliance cache decision result;

[0104] Among them, the resource balancing factor of each roadside base station is:

[0105] ε j =(B1)+(1-α)(2)

[0106] B1=max(x k L) / j

[0107]

[0108] Among them, ε j is the resource balancing factor of the jth roadside base station; B1 is the ratio of the content storage capacity to the transmission capacity in the roadside base station; B2 is the total storage capacity utilization rate of the roadside base station; x k is the number of content blocks stored in the jth base station;

[0109] The resource balancing factor of each roadside base station is compared with the preset resource utilization threshold. If the resource balancing factor of a roadside base station is less than the preset resource utilization threshold, the roadside base station is removed from the corresponding base station alliance. That is, when the resource balancing factor of the roadside base station is less than the preset resource utilization threshold, the roadside base station leaves the corresponding base station alliance, and an updated alliance structure between base stations is obtained.

[0110] Step 4: Repeat steps 1-3 until the alliance structure between the updated base stations does not change any more, that is, the Pareto optimal structure is reached.

[0111] Step 5: Repeat the operation of step 2 to determine the content to be stored by each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result.

[0112] Step 6: Divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, store the number of content blocks of the same size in a number of base station alliances in the updated alliance structure between base stations, so as to obtain the Internet of Vehicles collaborative resource allocation result.

[0113] Specifically, each to-be-requested content is divided into a number of content blocks of the same size using the fountain coding method, that is, a number of content blocks of the same size are obtained; according to the updated cache decision result, the number of content blocks of the same size are stored in a number of base station alliances in the updated alliance structure between base stations.

[0114] In the present invention, after each content to be requested is divided by the fountain coding method, each content to be requested is divided into a number of content blocks of the same size, and the content blocks are placed in each roadside base station according to the cache decision; wherein the size of each content block is L; that is, the content block quantity vector N of all the content to be requested is:

[0115] N={n1,n2,…,n e}

[0116] Among them, n e is the number of content blocks of the content to be requested with sequence number e.

[0117] Therefore, the end-user vehicle restores the content blocks required for the original content according to the content block quantity vector N of all the content to be requested.

[0118] Step 7: The end-user vehicle communicates with multiple roadside base stations along the way during driving, so as to download the complete required content. Specifically, since the channel state changes rapidly during driving, the end-user vehicle sends the content demand and basic information of the end-user vehicle to the remote cloud before entering the coverage area of ​​the roadside base station, and then communicates with multiple roadside base stations that have stored the required content blocks during driving to obtain the complete required content. The end-user vehicle s j Payment is made after the complete content block is acquired.

[0119] In the present invention, the set of terminal user vehicles that are about to enter the range of the roadside base station is defined as S = {s1, s2, ..., s n}, the demand content of the end-user vehicle is c j ; Assumption: The traffic density of vehicles on the road is vehicles / meter, and they travel independently at a constant speed; wherein the constant speed is calculated according to the Greenshields speed-density relationship model:

[0120] Wherein, the constant speed is:

[0121]

[0122] Among them, v f Indicates the speed of the vehicle when the road is clear, taking the maximum speed limit of the road; ρ jam Indicates the vehicle density under traffic congestion conditions.

[0123] A simulation communication model is constructed based on the actual highway scene. Specifically, in the highway vehicle scene, there are few road obstructions and the signal transmission can be regarded as free space propagation. Therefore, the free space path loss model is used to calculate the terminal user vehicle s at time t. j and roadside base station i The channel gain P G ;

[0124] Among them, the terminal user vehicle s at time t j and roadside base station i The channel gain P G for:

[0125]

[0126] Among them, P t is the transmission power of the roadside base station.

[0127] According to Shannon's theorem, calculate the terminal user vehicle s at time tj and roadside base station i The transmission rate between ij (t); where, at time t, the terminal user vehicle s j and roadside base station i The transmission rate between ij (t) is:

[0128]

[0129] Among them, σ 2 is the Gaussian noise power; W is the communication bandwidth.

[0130] When the distance d between the roadside base station and the end user's vehicle ij (t) is smaller than the base station coverage radius R i When the end-user vehicle s j With roadside base station i Communication is possible, and the communication time is t ij ; Calculate the total transmission volume B based on the transmission rate and the driving time integration ij for:

[0131]

[0132] When the roadside base station i The cache decision vector is The end-user vehicle s j During driving, the number of content blocks obtained is o, which is transmitted with each roadside base station. ij for:

[0133]

[0134] Among them, the roadside base station r i With end-user vehicles j The maximum amount of data that can be transferred between two packets; L is the content block size.

[0135] If the content required by the end-user vehicle has been cached in the roadside base station, the end-user vehicle communicates with multiple roadside base stations of the same alliance to obtain the complete content block. j Payment is made after the complete content block is acquired.

[0136] Among them, the total revenue u(x) obtained by the base station is:

[0137]

[0138] Among them, β i Whether the vehicle can obtain the complete content block, if yes, it is 1, otherwise it is 0; For content c i Download fee.

[0139] Among them, the total system cost cost(x) is:

[0140]

[0141] Among them, is the coefficient that converts transmission energy consumption into overhead; is the transmission power of the roadside base station; t i,j is the transmission time between the base station and the end-user vehicle.

[0142] The Internet of Vehicles collaborative resource allocation method described in the present invention utilizes the transmission and storage capacity limitations of edge base stations, and forms an alliance according to the content required by the vehicle to obtain a resource allocation result, thereby improving resource utilization and optimizing user experience; in the present invention, for large file transmission in high-speed scenarios, a roadside base station cooperative content placement model is established, so that the roadside base stations can jointly complete content transmission under distributed cooperation; wherein, an alliance is formed in a complementary manner through edge base stations, and content caching decisions are made according to the formed alliance, ensuring that as much content as possible can be placed under the condition of complete transmission, and maximizing system benefits under the random content needs of vehicles; resource allocation in the Internet of Vehicles edge caching scenario that meets the high-speed form of vehicles reduces user latency, ensures transmission efficiency and user experience, reduces the overall system cost, and improves system benefits and resource utilization.

[0143] The present invention also provides a vehicle network collaborative resource allocation system, including an alliance construction module, a cache decision module, an alliance update module, a first operation repetition module, a second operation repetition module and a resource allocation module; the alliance construction module is used to construct an alliance structure between base stations based on the cacheable content, storage capacity and transmission volume between the terminal user vehicles of the plurality of roadside base stations, with the maximum roadside base station revenue as the objective function; wherein the alliance structure between the base stations includes a plurality of base station alliances; the cache decision module is used to make a cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result; the alliance update module is used to use a resource balancing method to allocate cache decisions based on the alliance cache decision result to the base stations with low resource utilization and low resource utilization. The base station alliance with a preset threshold is split and updated to obtain an updated alliance structure between base stations; a first operation repetition module is used to repeat the operations of the alliance construction module, the cache decision module and the alliance update module until the updated alliance structure between base stations no longer changes; a second operation repetition module is used to repeat the operations of the cache decision module to determine the content to be stored in each base station alliance in the updated alliance structure between base stations to obtain an updated cache decision result; a resource allocation module is used to divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, the number of content blocks of the same size are stored in a number of base station alliances in the updated alliance structure between base stations, that is, the Internet of Vehicles collaborative resource allocation result is obtained.

[0144] The present invention also provides a vehicle networking collaborative resource allocation device, comprising: a memory for storing a computer program; and a processor for implementing the steps of the vehicle networking collaborative resource allocation method when executing the computer program.

[0145] When the processor executes the computer program, the steps of the above-mentioned vehicle network collaborative resource allocation method are implemented, for example: step 1, according to the cacheable content, storage capacity and transmission volume between the terminal user vehicle and the plurality of roadside base stations, with the maximum roadside base station revenue as the objective function, an alliance structure between base stations is constructed; wherein the alliance structure between base stations includes a plurality of base station alliances; step 2, according to a preset content placement algorithm, a cache decision is made, the content to be stored by each base station alliance in the alliance structure between base stations is determined, and an alliance cache decision result is obtained; step 3, according to the alliance cache decision result, a resource balancing method is used to allocate resources to the alliance with a resource utilization rate below a preset threshold. Step 4: repeat the operations of steps 1-3 until the updated alliance structure between base stations no longer changes; Step 5: repeat the operation of step 2 to determine the content to be stored in each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result; Step 6: divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, store the number of content blocks of the same size in a number of base station alliances in the updated alliance structure between base stations, that is, obtain the Internet of Vehicles collaborative resource allocation result.

[0146] Alternatively, when the processor executes the computer program, the functions of each module in the above system are implemented, for example: an alliance construction module, which is used to construct an alliance structure between base stations based on the cacheable content, storage capacity and transmission volume between the terminal user vehicles of the plurality of roadside base stations, with the maximum roadside base station revenue as the objective function; wherein the alliance structure between the base stations includes a plurality of base station alliances; a cache decision module, which is used to make a cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result; an alliance update module, which is used to split and update the base station alliances with low resource utilization and a preset threshold according to the alliance cache decision result using a resource balancing method, and obtain to the updated alliance structure between base stations; a first operation repetition module, used to repeat the operations of the alliance construction module, the cache decision module and the alliance update module until the updated alliance structure between base stations no longer changes; a second operation repetition module, used to repeat the operations of the cache decision module, determine the content to be stored in each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result; a resource allocation module, used to divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, store the number of content blocks of the same size in a number of base station alliances in the updated alliance structure between base stations, that is, obtain the Internet of Vehicles collaborative resource allocation result.

[0147] Exemplarily, the computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments that can complete preset functions, and the instruction segments are used to describe the execution process of the computer program in the Internet of Vehicles collaborative resource allocation device. For example, the computer program can be divided into an alliance construction module, a cache decision module, an alliance update module, a first operation repetition module, a second operation repetition module and a resource allocation module; the specific functions of each module are as follows: an alliance construction module, which is used to construct an alliance structure between base stations based on the cacheable content, storage capacity and transmission volume between the terminal user vehicles of several roadside base stations, with the maximum roadside base station revenue as the objective function; wherein the alliance structure between the base stations includes several base station alliances; a cache decision module, which is used to make cache decisions according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain the alliance cache decision result; an alliance update module, which is used to use a resource balancing method to optimize resource utilization according to the alliance cache decision result. The base station alliances whose values ​​are lower than a preset threshold are split and updated to obtain an updated alliance structure between base stations; a first operation repetition module is used to repeat the operations of the alliance construction module, the cache decision module and the alliance update module until the updated alliance structure between base stations no longer changes; a second operation repetition module is used to repeat the operations of the cache decision module to determine the content to be stored in each base station alliance in the updated alliance structure between base stations to obtain an updated cache decision result; a resource allocation module is used to divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, the number of content blocks of the same size are stored in a number of base station alliances in the updated alliance structure between base stations to obtain the Internet of Vehicles collaborative resource allocation result.

[0148] The Internet of Vehicles collaborative resource allocation device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The Internet of Vehicles collaborative resource allocation device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above are examples of Internet of Vehicles collaborative resource allocation devices and do not constitute a limitation on the Internet of Vehicles collaborative resource allocation device. The Internet of Vehicles collaborative resource allocation device may include more components than the above, or a combination of certain components, or different components. For example, the Internet of Vehicles collaborative resource allocation device may also include input and output devices, network access devices, buses, etc.

[0149] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor is the control center of the Internet of Vehicles collaborative resource allocation device, and uses various interfaces and lines to connect the various parts of the entire Internet of Vehicles collaborative resource allocation device.

[0150] The memory can be used to store the computer program and / or module, and the processor implements various functions of the Internet of Vehicles collaborative resource allocation device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory.

[0151] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0152] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method for allocating collaborative resources in an Internet of Vehicles are implemented.

[0153] If the modules / units integrated in the Internet of Vehicles collaborative resource allocation system are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0154] Based on this understanding, the present invention implements all or part of the processes in the above-mentioned vehicle networking cooperative resource allocation method, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned vehicle networking cooperative resource allocation method can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0155] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0156] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0157] The Internet of Vehicles collaborative resource allocation method and system described in the present invention considers the end-edge-cloud collaborative architecture of Internet of Vehicles edge computing in a highway scenario, including a remote cloud, a roadside unit and terminal user vehicles; the roadside base station collects the current vehicle user movement speed and content demand, with maximizing the roadside base station revenue as the objective function; according to the communication transmission volume limit and the storage capacity limit, an alliance structure is autonomously formed through the optimized collaborative resource allocation algorithm; a greedy algorithm is used to make cache decisions for each formed base station alliance, and the content is divided into content blocks through fountain code encoding, and cached in different base stations; vehicle users communicate with multiple base stations along the way during driving to download complete content blocks; the present invention improves the revenue and resource utilization of the Internet of Vehicles edge base station system, and can still maintain high efficiency and stability of transmission in high-speed scenarios, effectively improving the user experience of terminal users.

[0158] In the present invention, while considering the system storage capacity constraints, the data transmission capacity limit between the vehicle and the base station is taken into account; the optimized collaborative matching method is adopted to enable the base stations to form an optimal alliance structure, thereby maximizing the resource utilization and benefits of the system; in the edge caching scenario of the Internet of Vehicles where the vehicle is running at high speed, the caching efficiency is improved, the data transmission and service quality are guaranteed, the delay for users to obtain content is reduced, and the user experience of the end users is effectively improved.

[0159] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.

Claims

1. A method for allocating collaborative resources in an Internet of Vehicles, characterized in that: Used in the collaborative resource allocation process in the edge computing network of the Internet of Vehicles; wherein the end-edge-cloud collaborative architecture of the edge computing network of the Internet of Vehicles includes a remote cloud, a number of roadside base stations and a number of end-user vehicles; the remote cloud, the number of roadside base stations and the number of end-user vehicles are interconnected by wireless communication; The Internet of Vehicles collaborative resource allocation method includes: Step 1: According to the cacheable content, storage capacity and transmission volume between the roadside base stations and the terminal user vehicle, an alliance structure between base stations is constructed with the maximum roadside base station revenue as the objective function; wherein the alliance structure between base stations includes a plurality of base station alliances; Step 2: Perform cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result; Step 3: According to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance whose resource utilization is lower than a preset threshold, so as to obtain an updated alliance structure between the base stations; Step 4: Repeat steps 1-3 until the alliance structure between the updated base stations does not change any more; Step 5: Repeat the operation of step 2 to determine the content to be stored by each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result; Step 6: Divide each content to be requested to obtain a number of content blocks of the same size; and store the number of content blocks of the same size in a number of base station alliances in the updated alliance structure between base stations according to the updated cache decision result, so as to obtain the Internet of Vehicles collaborative resource allocation result; In step 1, the objective function is: in, The optimization goal is to maximize the revenue of roadside base stations; Total revenue obtained for roadside base stations; is the total overhead of the roadside base station; For plans stored in The number of content blocks in each roadside base station; is constraint 1, i.e., the storage capacity limit of the roadside base station; is the content block size; For the The storage capacity of each roadside base station; The serial number is The content to be requested; is constraint 2, i.e., the maximum transmission volume between the roadside base station and the end user vehicle; For the A roadside base station and i Maximum transfer volume between end-user vehicles; Indicates whether the end-user vehicle can obtain the complete content block, with a value of 1 or 0; Request download content for end-user vehicles the cost of is the coefficient that converts transmission energy consumption into overhead; is the transmission power of the roadside base station; For the A roadside base station and i The transmission time between end-user vehicles; In step 1, according to the cacheable content, storage capacity and transmission volume between the roadside base stations and the terminal user vehicle, a collaborative matching algorithm is adopted to build an alliance structure between the base stations with the maximum roadside base station revenue as the objective function; The alliance structure between the base stations is: in, It is the alliance structure between base stations; For the Base station alliance; The construction process of each base station alliance is as follows: According to the cacheable content, storage capacity and transmission volume between the roadside base station and the terminal user vehicle, a matching factor of each roadside base station is set; and roadside base stations with similar matching factors are grouped as a base station alliance; Among them, The matching factor of a roadside base station is: in, For the Matching factor of roadside base stations; is the parameter factor; For the The storage capacity of each roadside base station; For the The amount of transmission between a roadside base station and a passing end-user vehicle; In step 2, a cache decision is made according to a preset content placement algorithm to determine the content to be stored by each base station alliance in the alliance structure between the base stations. In the process of obtaining the alliance cache decision result, the preset content placement algorithm is a greedy algorithm; The specific process is as follows: Get the total storage of each base station alliance in the alliance structure between the base station alliances and total transfer volume ; Calculate the revenue of each content to be requested, and sort all the content to be requested according to the revenue of each content to be requested to obtain a content revenue sorting result; According to the content revenue ranking result, according to the total storage space of each base station alliance in the alliance structure between the base station alliances and total transfer volume , all the content to be requested is stored in the base station alliance with the closest storage capacity and transmission capacity, and the alliance cache decision result is obtained; wherein the alliance cache decision result includes the base station alliance cache decision vector and the roadside base station cache decision vector.

2. A method for allocating cooperative resources in an Internet of Vehicles according to claim 1, characterized in that: In step 3, according to the alliance cache decision result, a resource balancing method is used to split and update the base station alliance with low resource utilization and a preset threshold, and the process of obtaining the updated alliance structure between the base stations is as follows: Calculating a resource balancing factor of each roadside base station according to the alliance cache decision result; The resource balancing factor of each roadside base station is compared with the preset resource utilization threshold. If the resource balancing factor of a roadside base station is less than the preset resource utilization threshold, the roadside base station is removed from the corresponding base station alliance to obtain an updated alliance structure between base stations.

3. A method for allocating cooperative resources in an Internet of Vehicles according to claim 2, characterized in that: The resource balancing factor of each roadside base station is: = in, For the Resource balancing factor of roadside base stations; is the ratio of content storage to transmission volume in the roadside base station, is the total storage capacity utilization rate of the roadside base station; x k To store in The number of content blocks in a base station.

4. The method for allocating cooperative resources in an Internet of Vehicles according to claim 1, characterized in that: The process of dividing each content to be requested to obtain several content blocks of the same size is as follows: By using the fountain coding method, each content to be requested is divided into a number of content blocks of the same size, that is, a number of content blocks of the same size are obtained.

5. A vehicle networking collaborative resource allocation system, characterized in that: Used in the collaborative resource allocation process in the edge computing network of the Internet of Vehicles; wherein the end-edge-cloud collaborative architecture of the edge computing network of the Internet of Vehicles includes a remote cloud, a number of roadside base stations and a number of end-user vehicles; the remote cloud, the number of roadside base stations and the number of end-user vehicles are interconnected by wireless communication; The Internet of Vehicles collaborative resource allocation system includes: An alliance building module is used to build an alliance structure between base stations based on the cacheable content, storage capacity and transmission volume between the end-user vehicles of the roadside base stations, taking the maximum roadside base station revenue as the objective function; wherein the alliance structure between the base stations includes a plurality of base station alliances; A cache decision module, used to make a cache decision according to a preset content placement algorithm, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and obtain an alliance cache decision result; An alliance updating module is used to split and update the base station alliances with low resource utilization and a preset threshold according to the alliance cache decision result and use a resource balancing method to obtain an updated alliance structure between the base stations; A first operation repetition module, used to repeat the operations of the alliance construction module, the cache decision module and the alliance update module until the alliance structure between the updated base stations does not change any more; A second operation repeating module, configured to repeat the operation of the cache decision module, determine the content to be stored by each base station alliance in the updated alliance structure between base stations, and obtain an updated cache decision result; A resource allocation module is used to divide each content to be requested to obtain a number of content blocks of the same size; and according to the updated cache decision result, the number of content blocks of the same size are stored in a number of base station alliances in the updated alliance structure between base stations, that is, to obtain the Internet of Vehicles collaborative resource allocation result; The objective function is: in, The optimization goal is to maximize the revenue of roadside base stations; Total revenue obtained for roadside base stations; is the total overhead of the roadside base station; For plans stored in The number of content blocks in each roadside base station; is constraint 1, i.e., the storage capacity limit of the roadside base station; is the content block size; For the The storage capacity of each roadside base station; The serial number is The content to be requested; is constraint 2, i.e., the maximum transmission volume between the roadside base station and the end user vehicle; For the A roadside base station and i Maximum transfer volume between end-user vehicles; Indicates whether the end-user vehicle can obtain the complete content block, with a value of 1 or 0; Request download content for end-user vehicles the cost of is the coefficient that converts transmission energy consumption into overhead; is the transmission power of the roadside base station; For the A roadside base station and i The transmission time between end-user vehicles; According to the cacheable content, storage capacity and transmission volume between the roadside base stations and the terminal user vehicle, a collaborative matching algorithm is adopted to build an alliance structure between the base stations with the maximum roadside base station revenue as the objective function; The alliance structure between the base stations is: in, It is the alliance structure between base stations; For the Base station alliance; The construction process of each base station alliance is as follows: According to the cacheable content, storage capacity and transmission volume between the roadside base station and the terminal user vehicle, a matching factor of each roadside base station is set; and roadside base stations with similar matching factors are grouped as a base station alliance; Among them, The matching factor of a roadside base station is: in, For the Matching factor of roadside base stations; is the parameter factor; For the The storage capacity of each roadside base station; For the The amount of transmission between a roadside base station and a passing end-user vehicle; The preset content placement algorithm is used to make a cache decision, determine the content to be stored by each base station alliance in the alliance structure between the base stations, and in the process of obtaining the alliance cache decision result, the preset content placement algorithm is a greedy algorithm; The specific process is as follows: Get the total storage of each base station alliance in the alliance structure between the base station alliances and total transfer volume ; Calculate the revenue of each content to be requested, and sort all the content to be requested according to the revenue of each content to be requested to obtain a content revenue sorting result; According to the content revenue ranking result, according to the total storage space of each base station alliance in the alliance structure between the base station alliances and total transfer volume , all the content to be requested is stored in the base station alliance with the closest storage capacity and transmission capacity, and the alliance cache decision result is obtained; wherein the alliance cache decision result includes the base station alliance cache decision vector and the roadside base station cache decision vector.

6. A vehicle networking cooperative resource allocation device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the vehicle network collaborative resource allocation method as described in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the vehicle network collaborative resource allocation method as described in any one of claims 1 to 4 are implemented.

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