CN116709532A - Data scheduling method based on conflict graph and clustering in Internet of vehicles environment - Google Patents

Data scheduling method based on conflict graph and clustering in Internet of vehicles environment Download PDF

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CN116709532A
CN116709532A CN202310987286.6A CN202310987286A CN116709532A CN 116709532 A CN116709532 A CN 116709532A CN 202310987286 A CN202310987286 A CN 202310987286A CN 116709532 A CN116709532 A CN 116709532A
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rsu
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丁煦
郑祥
徐鹏飞
张碧珣
刘庆华
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Zhongke Xingtu Ruiyun Technology Co ltd
Hefei University of Technology
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Hefei University of Technology
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    • H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/46—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
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    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
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    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
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    • H—ELECTRICITY
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    • H04W72/569—Allocation or scheduling criteria for wireless resources based on priority criteria of the information or information source or recipient of the traffic information
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention relates to the technical field of digital information transmission, in particular to a data scheduling method based on conflict graphs and clusters in an Internet of vehicles environment, which comprises the following operation steps: s1, acquiring digital information data transmitted in an experimental area; s2, establishing a conflict graph of the related RSU node and the vehicle node through centralized scheduling in the coverage area of the RSU, and carrying out digital information data transmission according to a data transmission mode in the conflict graph; s3, establishing clusters associated with all vehicle nodes through self-organizing scheduling synchronously carried out with centralized scheduling in an RSU blind area, and sending data for the vehicle nodes in the clusters which run in opposite directions through the vehicle nodes in the clusters; according to the invention, according to the real-time physical topology and data request among vehicles, the vehicles can perform high-efficiency data sharing under the condition of avoiding transmission conflict, and meanwhile, the vehicles in the RSU zone can enhance the opportunity of acquiring data by the vehicles in the RSU zone in a mode of forwarding the data carried by the vehicles to the RSU zone.

Description

Data scheduling method based on conflict graph and clustering in Internet of vehicles environment
Technical Field
The invention relates to the technical field of digital information transmission, in particular to a data scheduling method based on conflict graphs and clusters in an Internet of vehicles environment.
Background
Autopilot can reduce traffic collisions and labor costs to some extent through a large amount of information interaction between vehicles, and at the same time improve the efficiency of traffic management. Among the information interaction technologies commonly used are VANET, which is a wireless network where multiple access technologies coexist with multiple protocols, and can implement information interaction between vehicles through V2C, V I and V2V communication. Through the interaction of the information, the central server can effectively monitor various states of the running vehicles on the road, so that safe, intelligent and personalized driving and traveling processes are realized.
Effective data transmission is critical to autopilot service, and many researches are focused on improving the reliability and quality of V2I and V2V communication; there is also much research focused on V2I and V2V collaboration, and on data scheduling for multi-hop V2V; in addition, some research has focused on edge-assisted scheduling algorithm research. While the above prior studies have put a great deal of effort into the transmission of information from vehicle networks, the inherent nature of the internet of vehicles presents a significant challenge for efficient data sharing. Firstly, due to the high-speed movement of vehicles, the physical topology and the channel quality between the vehicles are continuously changed, so that the time for stabilizing data transmission is shortened; meanwhile, the data request of the vehicle can also change along with the change of the state of the vehicle, so that the vehicle cannot receive the required data, and the accuracy of data transmission is reduced. Second, it becomes difficult to fully utilize wireless bandwidth due to communication constraints such as half duplex transmission and concurrent transmission interference of the OBU. In addition, although the RSU has the characteristics of wide communication range and rich resources, because the RSU is often sparsely deployed at higher cost, data cannot be acquired from the RSU after the vehicle leaves the coverage area of the RSU, so that the vehicle cannot timely select an optimal driving state according to real-time traffic conditions.
Disclosure of Invention
In order to avoid and overcome the technical problems in the prior art, the invention provides a data scheduling method based on conflict graphs and clusters in an Internet of vehicles environment. The invention can lead the vehicles to carry out accurate and efficient data sharing, and simultaneously lead the vehicles in the RSU blind area to carry out data transmission.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the data scheduling method based on the conflict graph and the clustering in the car networking environment comprises the following operation steps:
s1, acquiring digital information data in an experimental area;
s2, establishing a conflict graph of the related RSU node and the vehicle node through centralized scheduling in the coverage area of the RSU, and carrying out digital information data transmission according to a data transmission mode in the conflict graph;
s3, establishing clusters associated with all vehicle nodes through self-organizing scheduling synchronously carried out with centralized scheduling in an RSU blind area, and sending data for the vehicle nodes in the clusters which run in opposite directions through the vehicle nodes in the clusters.
As still further aspects of the invention: the specific steps of step S1 are as follows:
s11, selecting a road with a set length as an experimental area;
s12, installing a base station in an experimental area, collecting and processing digital information data in real time by the base station through V2C communication, and storing the digital information data in a database;
S13, sequentially deploying RSUs along roads as RSU nodes, and connecting the RSUs with a base station through a wired link to obtain real-time digital information data from the base station; taking the digital information data as a data source, and serving vehicle nodes in the coverage area of the RSU node through V2I communication;
s14, determining the number of RSU nodes in the experimental area, and storing each RSU node in an RSU node setRIn the process, R={R 1 ,…,R i ,…,R n }，R 1 representing the 1 st RSU node in the experimental area,R i representing the first of the experimental zoneiThe number of RSU nodes is one,R n representing the first of the experimental zonenA plurality of RSU nodes;
s15, determining the number of vehicle nodes in the experimental area, and storing each vehicle node in a vehicle node setVIn the process, V={V 1 ,…,V i ,…,V m }，V 1 representing the 1 st vehicle node in the experimental area,V i representing the first of the experimental zoneiThe number of vehicle nodes in the vehicle is,V m representing the first of the experimental zonemA plurality of vehicle nodes;
s16, storing the RSU nodes and the vehicle nodes in the test area in the total node set in sequenceNIn the process, N={N 1 ,…,N i ,…,N j ,…,N m+n }，N=R∪V，N 1 representing the 1 st node in the experimental area,N i representing the first of the experimental zoneiThe number of nodes in the network is,N j representing the first of the experimental zonejThe number of nodes in the network is,N m+n representing the first of the experimental zonem+nA plurality of nodes;
s17, equally dividing digital information data in the database into sub DThe I term, each part of size isd size And sequentially stored in a data setDIn the process, D={d 1 ,…,d i ,…,d |D| }，d 1 representing a datasetDIn the item 1 of the data,d i representing a datasetDThe first of (3)iThe data of the item(s),d |D| representing a datasetDOf the first part of the seriesDData of the I item; nodeN i The cached data item set formed by the cached digital information data isα(N i ) NodeN i The requested data item set composed of the requested digital information data isβ(N i ) And nodeN i Neighbor set of adjacent nodes isΩ(N i )={N j |d i j, ≤d v2v ,N j ∈NAnd } wherein,d i j, representing nodesN i Sum nodeN j The communication distance between the two-way communication device and the base station,d v2v representing V2V communication distance.
As still further aspects of the invention: when the vehicle node enters the coverage area of the RSU node, V2I communication can be carried out between the vehicle node and the RSU node or V2V communication can be carried out between the vehicle node and the neighbor vehicle node, so that the required digital information data can be obtained; this process of transmitting data via V2I or V2V communication is calledPT，PTThe expression is as follows:
wherein, representing nodesN i A kind of electronic devicePT；Representing nodesN i A set of transmitted data items constituted by the transmitted digital information data;Is->Is a triplet of (3);Representing a receiving nodeN i A received data item set formed by the digital information data received by the vehicle node of the transmitted digital information data;
RSU nodeR i All within a coverage areaPTThe formed candidate scheduling set is ，，Representing RSU nodesR i 1 st in coverage areaPT，Representing RSU nodesR i Within the coverage areaωPersonal (S)PT，Representing RSU nodesR i Within coverage area->Personal (S)PT；
Under the condition of meeting communication constraint, RSU node is selected through centralized schedulingR i The candidate scheduling set isNot interfere with each otherPTConstitutes a centralized scheduling set->，The expression is as follows:
wherein, representing RSU nodesR i One time in coveragePTA total number of valid data items that all receiving nodes can receive,I(. Cndot.) is shown at this timePTAnd the influence on data scheduling in the RSU blind area.
As still further aspects of the invention: the specific process of centralized scheduling in the coverage area of the RSU is as follows:
S2A1, a base station obtains context information of each node, wherein the context information comprises signal-to-noise ratio of the node; the signal-to-noise ratio is used for obtaining the channel quality capacity among the nodes, and the calculation formula of the channel quality capacity is as follows:
wherein, C i j, representing nodesN i Sum nodeN j The capacity of the channel quality in between,SINR i j, representing nodesN i Sum nodeN j Signal to noise ratio between;
S2A2, then calculate the realityScheduling cycles within a test areaTThe maximum data item number which can be transmitted between any two nodes is calculated as follows:
wherein, η i j, Representing nodesN i Sum nodeN j The maximum number of data items that can be transmitted between;
S2A3, constructing an undirected graph according to the context information of each node obtained by the base stationUG(N,E UG ) Undirected graphUG(N,E UG ) Two adjacent nodes are connected with each other through a transmission link;
S2A4, judging whether the transmission link is effective according to a judging criterion, and calculating the number of maximum data items which can be actually transmitted between two nodes in the effective transmission link, wherein the calculation formula is as follows:
wherein, lambda i j, Representing nodesN i To the nodeN j The maximum number of data items that can actually be transmitted by the transmission link of (a) isα(N i ) I represents a nodeN i The number of cached data items;
judgment criteria: if the number of data items owned by a sender node for sending digital information data in a transmission link is smaller than the maximum number of data items which can be transmitted between two nodes of the transmission link, or the digital information data cannot be transmitted between the two nodes, the transmission link is invalid, otherwise, the transmission link is valid;
S2A5 according to undirected graphUG(N,E UG ) In the effective transmission link and the transmission direction of the effective transmission link, the undirected graphUG(N,E UG ) Conversion to a directed graphDG(N,E DG )；
S2A6, on the premise of meeting communication constraint, mapping the directed graphDG(N,E DG ) Conversion to conflict graphG I And calculating effective data actually received by the receiver node, and storing the effective data in an effective data set, wherein the calculation formula of the effective data set is as follows:
Wherein, representing nodesN i Send->Giving nodesN j When the nodeN j A set of valid data actually received;
S2A7, then calculatePTIs used for the weight of the (c),PTthe weight of (1) comprises a quantity weight and an influence weight on an RSU blind area, and the calculation formula of the quantity weight is as follows:
the calculation formula of the influence weight on the RSU blind area is as follows:
PTthe weights of (2) are calculated as follows:
wherein, representation and vehicle nodeV j A set of vehicle nodes traveling in opposite directions;V S is->Middle (f)SA plurality of vehicle nodes;Representing vehicle nodesV S A requested collection of data items;U i representing the first in the conflict graphiA plurality of nodes;W(U i ) Representing nodesU i Is a weight of (2).
As still further aspects of the invention: directed graphDG(N,E DG ) Conversion to conflict graphG I The steps of (a) are as follows:
S2B1, firstly calculating each through a judgment criterionPTEach element in the triplet of (2);
judgment criterion one:i.e. nodesN i The transmitted data belonging to a nodeN i Buffering data in a set of data items;
judgment criterion II:，representing nodesN i The number of data items in the set of transmitted data items constituted by the transmitted digital information data,Ω(N i ,DG) Representation belongs to a directed graphDG(N,E DG ) Middle nodeN i Neighbor sets, i.e. nodesN i The number of data items transmitted belongs to the directed graphDG(N,E DG ) Middle node N i Any one of the neighbor edge weights;
S2B2, then calculateAnd pass->Calculate->，The calculation formula of (2) is as follows:
the calculation formula of (2) is as follows:
wherein, Ω(N i ,DG) Representation belongs to a directed graphDG(N,E DG ) Middle nodeN i Is a neighbor set of (a);
S2B3 due to differencesPTMutual interference exists between the two communication nodes, so that collision is caused, and therefore, communication constraint for eliminating the collision is set to avoid the occurrence of the collision, and the communication constraint is as follows:
constraint one: same scheduling periodTIn the meantime, the same node cannot simultaneously transmit and receive data;
constraint II: same scheduling periodTEach node can only transmit one group of data items at a time;
constraint three: same scheduling periodTIn the method, the same node cannot simultaneously receive data sent by a plurality of nodes;
S2B4, according to communication constraint, conflict exists between any twoPTAdding an edge between nodes to represent that transmission conflicts exist; traversing all conflicts in RSU coveragePTNodes and corresponding edges are drawn to form a conflict graphG I 。
As still further aspects of the invention: after the calculation is completedPTAfter the weights of (2), solving the maximum weighted independent set by using a marking algorithm, wherein the specific steps are as follows:
S2C1, initializing a conflict graph, and marking all nodes as unaccessed;
S2C2, calculating each nodeW(U i )/(d(U i )+1) A value of whereind(U i ) Representative nodeU i Degree of (3);
S2C3 selection from non-accessed nodesW(U i ) Adding the largest node into the initial independent set, and marking the newly added node and the adjacent nodes as accessed nodes;
S2C4, repeating the step S2C3 until all nodes are marked as accessed;
S2C5, enabling the initial independent set to be the maximum weighted independent set, and determining a sending node, a sent data set and a receiving node to share data according to each node in the maximum weighted independent set.
As still further aspects of the invention: the cluster is established by adopting a clustering algorithm, and the cluster establishment process is as follows:
s31, acquiring and vehicle nodeV i Neighbor set formed by adjacent vehicle nodes, wherein the neighbor set isΩ(V i )={V j |d i j, ≤d v2v ,V j ∈VIf (3)Ω(V i ) Empty set, then vehicle nodeV i As a cluster head; otherwise, go to step S32;
s32, calculating a non-empty setΩ(V i ) Average link similarity of each vehicle node in (a) if the vehicle nodeV i If the average link similarity of the (a) is maximum, the vehicle node is determined to beV i As a cluster head; otherwise, step S33 is entered;
the average link similarity calculation formula is as follows:
wherein, indicating the first place in the RSU blind areaiAverage link similarity of adjacent vehicle nodes in the communication range of each vehicle node; n i For nodes in RSU blind area and vehicleV i The number of adjacent vehicle nodes;DLS i j, vehicle node in RSU blind areaV i And vehicle nodeV j Link similarity between the two;DLS i j, vehicle node in RSU blind areaV i And vehicle nodeV j Link similarity between the two;β(V i ) Vehicle node in RSU blind areaV i A request data item set formed by the requested digital information data;β(V i ) Vehicle node in RSU blind areaV i A request data item set formed by the requested digital information data;A i j, vehicle node in RSU blind areaV i And vehicle nodeV j Request similarity between;LDT i j, vehicle node in RSU blind areaV i And vehicle nodeV j A vehicle link duration therebetween;S i j, representing vehicle nodesV i And vehicle nodeV j A speed difference therebetween;
s33, selecting a non-empty setΩ(V i ) The average link similarity is greater than the vehicle nodeV i And store the node setsMIn (a) and (b);
s34, judging node setMIf there is cluster head in the network, if there is cluster head, then vehicle nodeV i Adding the components with the maximum valueDLSCluster head of valueIs the opposite of the cluster of vehicle nodesV i As a cluster head.
As still further aspects of the invention: in an RSU blind area, after a clustering algorithm of a vehicle node based on link similarity finishes clustering, the motion characteristics of cluster members are kept unchanged, the vehicle node selected as a cluster head maintains the position of the own cluster head, a non-cluster head node dynamically exits and joins the cluster according to the situation, and the non-cluster head node judges whether a cluster maintenance mechanism is required or not through periodically obtained beacon data; the cluster maintenance mechanism is performed in two cases:
First case: when common members of a clusterV j And cluster headCH k Is beyond the V2V communication rangeV j Exiting the current cluster and attempting to join the remaining clusters around; if there are no clusters around, then the general memberV j Generating a cluster by oneself as a cluster head;
second case: second case: after cluster generation, a threshold is setλThe method comprises the steps of carrying out a first treatment on the surface of the If common members of a clusterV j Other cluster heads exist nearby, andV j with the other cluster headDLSA value greater thanV j With the current cluster headDLSValue of two at the same timeDLSThe difference between the values is greater thanλ，Then cluster switching is performed; otherwise, cluster switching is not performed.
As still further aspects of the invention: after the cluster is generated, the service capacity of each vehicle node in the cluster is calculated, and the calculation process is as follows:
selecting clustersC k Vehicle node in (a)V i And will be in communication with the vehicle nodeV i Clusters running in opposite directions are stored in a collectionFor a pair ofCluster->Use->Representing the requested data set in the cluster;β m is->Uses +.>Representation ofβ m According to the amount of data requestedα(V i ) And->Computing vehicle nodesV i Is to be used for the service capability of:
wherein, SC(V i ) Representing vehicle nodesV i I.e. the maximum number of data items that a vehicle node in a cluster can transmit;
the vehicle node with the largest service capability is selected as a sender node for sending data, and corresponding data items are broadcasted to serve the clusters running in opposite directions when meeting the clusters running in opposite directions.
As still further aspects of the invention: the data transmission mode in the experimental area comprises centralized scheduling and self-organizing scheduling, wherein the centralized scheduling and the self-organizing scheduling form a centralized and self-organizing type cooperative scheduling problem, and the overall targets of the centralized and self-organizing type cooperative scheduling problem are as follows:
wherein, Urepresenting the maximum number of data items that can be transmitted in the experimental area;representing clustersC k The number of data items transmitted by the vehicle node having the greatest service capability.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides a framework based on the cooperative data sharing of an RSU coverage area and an RSU blind area, which can coordinate the centralized scheduling in the RSU coverage area and the self-organizing scheduling of the RSU blind area. And when the centralized scheduling is carried out, the priority of the data scheduling related to the RSU blind area request is improved by considering the data request of the vehicle in the RSU blind area, so that the vehicle carries related data to the RSU blind area for forwarding, and the opportunity of the RSU blind area vehicle for carrying out V2V data sharing is enhanced.
2. For centralized scheduling in the RSU coverage area, according to the real-time physical topology, channel quality and data request of the vehicle, a global network topology can be constructed efficiently, and transmission conflicts are modeled by using the global network topology to form a conflict graph. In the conflict graph, nodes represent data transmission services and edges represent transmission conflicts. The data sharing problem is converted into the maximum weighted independent set problem in the graph theory through the constructed conflict graph, and the maximum weighted independent set problem is solved, so that an optimal transmission path can be obtained under the condition of meeting communication constraint according to the real-time network topology.
3. Aiming at self-organizing scheduling in RSU blind area, the concept of link similarity is introduced to support better data sharing. Vehicles are clustered based on their physical information such as location, speed, direction, and network information such as requests and cached data items, with similarly requested vehicles being clustered together. Then, the vehicle with the largest service capability is selected in the cluster, and V2V data sharing is performed to the vehicles in the cluster. By adopting the mode, the same or similar data can be sent to the whole cluster at one time, so that the repetition and redundancy of data transmission are reduced, and the data sharing efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of the operation flow structure of the present invention.
Fig. 2 is an undirected graph in the present invention.
Fig. 3 is a directed graph in the present invention.
Fig. 4 is a conflict graph in the present invention.
FIG. 5 is a flow chart of cluster construction in accordance with the present invention.
FIG. 6 is a flow chart of a cluster maintenance mechanism in accordance with the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 to 6, a data scheduling method based on conflict graphs and clusters in an internet of vehicles environment comprises the following specific contents:
1. system architecture
The system structure formed by arranging hardware in an experimental area is mainly divided into three layers:
the first layer is a base station BS where one MEC server is deployed, and global digital information data is collected and processed in real time through V2C, so that all nodes in an experimental area are controlled in a centralized manner.
The second layer is an RSU which is sparsely deployed along the road, is used as a special sensing or data transmission node, is connected with the base station BS through a wired link, can obtain the latest and complete data from the base station BS, and is used as a data source to serve vehicles in the coverage area through V2I communication.
The third tier includes vehicles configured with GPS and OBU, which acquire data from RSU or neighboring vehicles via V2I/V2V communications.
RSU node and vehicle node in experimental area are respectively usedR={R 1 ,…,R i ,…,R n Sum ofV={V 1 ,…,V i ,…,V m The total number of nodes in the experimental area is indicated byN={N 1 ,…,N i ,…,N j ,…,N m+n And } represents. Equally dividing digital information data in a database into subDThe I term is the size of each partd size And sequentially stored in a data setDIn the process, D={d 1 ,…,d i ,…,d |D| }. NodeN i The cached data item set formed by the cached digital information data is α(N i ) NodeN i The requested data item set composed of the requested digital information data isβ(N i ) And nodeN i Neighbor set of adjacent nodes isΩ(N i )={N j |d i j, ≤d v2v ,N j ∈NAnd } wherein,d i j, representing nodesN i Sum nodeN j The communication distance between the two-way communication device and the base station,d v2v representing V2V communication distance.
When the vehicle enters the coverage area of the RSU, V2I communication can be carried out with the RSU or V2V communication can be carried out with the neighbor vehicle to obtain the required digital information data. Such a service of transmitting data through V2I or V2V communication is called Possible Transfers #PT) Once expressed by the following formulaPT：
Each of which isPTWith a tripletAnd (3) representing.N i Representing the node that sent the data, i.e. the sender of the data, is either an RSU node or a vehicle node.Representing nodesN i A set of transmitted data items constituted by the transmitted digital information data;Is->Is a triplet of (3);Representing a receiving nodeN i The digital information data is transmitted to the vehicle node, and the vehicle node receives the digital information data to form a received data item set.
Thus RSU nodeR i All within a coverage areaPTThe formed candidate scheduling set is，，Representing RSU nodesR i 1 st in coverage areaPT，Representing RSU nodesR i Within the coverage areaωPersonal (S)PT，Representing RSU nodesR i Within coverage area->Personal (S)PT。
Based on the above definition, the scheduling problem in the coverage area of the RSU can be expressed as follows: multiple presence for RSU coverage PTIt is desirable to select a number of transmissions from the candidate scheduling set that do not interfere with each other, as far as possible to satisfy the requests of the vehicle nodes, under the condition that the communication constraints are satisfied. Meanwhile, after the receiving party receives the data sent by the sending party, the number of vehicles in the RSU blind area is enhanced by carrying the data to the RSU blind areaAccording to the sharing opportunities. So RSU nodeR i Centralized scheduling within a coverage area is represented as follows:
wherein, representing RSU nodesR i One time in coveragePTA total number of valid data items that all receiver nodes can receive,I(. Cndot.) is shown at this timePTThe influence of the data item transmitted in the (B) on the data scheduling in the RSU blind area.
For self-organizing dispatch in the RSU blind area, when the vehicle node enters the RSU blind area, the data obtained from the coverage of the RSURSU can be transmitted to the vehicle nodes which run in opposite directions, so that the data sharing opportunity among the vehicle nodes in the RSU blind area is increased. Therefore, the self-organizing dispatch in the RSU blind area determines vehicles broadcasting data in the cluster and corresponding data items by dynamically constructing the cluster, and maximizes V2V data sharing to the maximum. In summary, the targets of performing self-organizing scheduling in the RSU blind area are as follows:
SC(V i ) Representing vehicle nodesV i Service capabilities, i.e. clustersC k Vehicle node in (a)V i The maximum number of data items that can be serviced by the vehicle nodes in the cluster traveling in opposite directions;
based on the above-mentioned RSU coverage area and RSU blind area problems, the centralized and self-organizing collaborative scheduling problem (CSC) is expressed as follows: in order to maximize the sum of the received valid data items, CSC enhances the opportunity of V2V data sharing in RSU blind areas by means of cooperative data distribution between RSU nodes and vehicle nodes and using a way that vehicle nodes travelling in opposite directions carry forwarding data, and maximally satisfies the requests of vehicle nodes, and the overall objective of CSC is expressed as follows:
for the centralized and self-organizing collaborative scheduling problem, we use centralized scheduling of RSU coverage area and self-organizing scheduling technique in RSU blind area to solve.
2. Centralized scheduling of RSU zones
And the base station BS performs centralized data scheduling on the vehicle nodes in the RSU coverage area according to the collected global information. First, an undirected graph is constructed using the network topology of the vehicle nodes and the associated context information. Second, the undirected graph is converted to a directed graph by eliminating some of the impractical transmission. And finally, constructing a conflict graph by using the obtained directed graph. Nodes in the conflict graph represent candidate scheduling sets In (a) and (b)PTEdges in the conflict graph represent conflicts between nodes due to wireless communication constraints. Based on the conflict graph, we can translate the centralized scheduling problem into a Maximum Weighted Independent Set (MWIS) problem and determine the communication mode and data transmission path of each vehicle by solving the MWIS problem. The specific process is as follows:
the base station BS obtains context information of each node, including a set of neighboring vehicles, a signal-to-noise ratio with each neighboring vehicle, a data item identifier of each neighboring vehicle node cache and request, and so on. Such as vehiclesN 2 Is { of neighbor setN 1 ,N 2 ,N 5 Corresponding signal-to-noise ratio is {SINR 2,1 ,SINR 2,3 ,SINR 2,5 The cached data item is {d 1 ,d 3 ,),(d 2 ),(d 3 ,d 4 (ii) and obtaining the channel quality capacity between the nodes through the signal-to-noise ratioC i j, ：
Wherein, C i j, representing nodesN i Sum nodeN j Channel quality capacity between.
From the information obtained above, a scheduling period can be calculatedTThe maximum number of data items which can be transmitted between any two nodes:
wherein, η i j, representing nodesN i Sum nodeN j The maximum number of data items that can be transmitted.
The base station BS collects the context information of all nodes to construct an undirected graphUG(N,E UG ) As shown in fig. 2. In undirected graphUG(N,E UG ) The number of data items owned by the sender node in some transmission links may be smaller than the maximum number of data items that can be transmitted between the nodes, or data cannot be transmitted between two nodes; such as nodes N 5 To the nodeN 3 In the transmission link of (3) |α(N 5 )|≤η 5,3 NodeN 1 To the nodeN 3 In the transmission link of (a) the transmission link of (c),α(N 1 )∩α(N 3 ) =0, so these transmission links are all inactive. So we want to go undirected graphUG(N,E UG ) Conversion to directed graphDG(N,E DG ) Eliminating part of the impractical transmission while reducing complexity.
For linksN i To the point ofN j Through lambda i j, Calculating the maximum number of data items which can be really transmitted:
according to lambda i j, Undirected graphUG(N,E UG ) Conversion to directed graphDG(N,E DG ) As shown in fig. 3.
2.1 construction of conflict graphs
In order to select a plurality of mutually non-interfering transmissions to fulfill a vehicle request under the condition of meeting communication constraints, the MEC server generates a directed graph according to the configurationDG(N,E DG ) Constructing a conflict graph on the premise of meeting judgment criteriaG I And through conflict graphG I And converting the data scheduling problem into a maximum weighted independent set problem to solve.
First, for eachPTIs a triplet of (3)We need to determine +.>And->，The following criteria are satisfied:
judgment criterion one: the data sent by the nodes are guaranteed to be owned by the nodes.
Judgment criterion II: ensuring that the number of data items sent by a node is a directed graphDG(N,E DG ) Middle nodeN i Any one of the neighbor edge weights, this criterion can reduce the number of nodes in the conflict graph, thereby reducing complexity.
Second, for each numberData item collectionOnly edge weights Λ i j, Is greater than->Can the neighbor node of (1) successfully receive the data, a +.>The expression is as follows:
the data actually received by the vehicle node may not be the data requested by itself due to the multicast transmission. For nodesN i TransmittingGiving nodesN j ，N j Effective data set received in practice>The calculation formula is as follows:
by following the following communication constraints, differentPTA conflict may occur between:
constraint one: same scheduling periodTIn which the same node cannot transmit and receive data at the same time. Such as
And->Representing nodesN i And is both a transmitting node and a receiving node.
Constraint II: same scheduling periodTIn which each node can only transmit one set of data at a timeAn item. Such asAndthen represent the nodeN i Multiple sets of data items are transmitted in the same scheduling period.
Constraint three: same scheduling periodTIn this case, the same node cannot simultaneously receive data transmitted from a plurality of nodes. Such asAnd->NodeN S Is multiple in number ofPTIs a recipient of (a).
Based on the above definition, a conflict graph is constructed by the following steps：
First, for each nodeFind the set of data items it may send +.>。
Second, forDifferent->Find its corresponding set of receiver nodes +. >Then the triplet->As a node in the conflict graph.
Finally, according to the communication constraint, at any placeMeaning that two exist in conflictPTAdding an edge between nodes represents a transmission collision.
Conflict graph constructed by the above stepsG I As shown in fig. 4.
2.2 marking Algorithm
Using conflict graphsG I We can model the centralized scheduling problem as an MWIS problem and solve it by a tagging algorithm to determine the communication mode and data transmission path of the vehicle. For each ofPTThe weight of the material is composed of two parts:
1) Currently, there is a need for a device for controlling the current state of the artPTNumber of requests that can be satisfied:
2) Impact on RSU blind zone vehicle requests
Wherein the method comprises the steps ofRepresentative and vehicleV j A set of vehicles traveling in a direction of opposite directions,V S is->Is provided.
Based on the above, a single PT node in the conflict graphU i The weight of (2) is:
after the node weights are defined, a labeling algorithm is used to solve the maximum weighted independent set problem:
and step 1, initializing a conflict graph, and marking all vertexes as unaccessed.
Step 2, for each vertex, calculateW(U i )/(d(U i )+1) A value of whereind(U i ) Representative nodeU i Is a degree of (3).
Step 3, selecting from the non-accessed nodesW(U i ) Adding the largest vertex into the independent set, and marking the newly added vertex and the adjacent vertex as accessed.
And 4, repeating the step 3 until all vertexes are marked as accessed.
And step 5, returning the selected independent set as the maximum weighted independent set, and determining a sending node, a sent data set and a receiving node of the independent set to share data according to each node in the maximum weighted independent set.
According to the centralized scheduling algorithm, vehicles in the range of the RSU do not need to contend for channels, data can be directly transmitted according to the scheduling result of the base station, and communication conflicts are avoided. Meanwhile, the data request of the vehicle in the RSU blind area is considered when the dispatching result is solved, so that the data sharing opportunity of the vehicle in the RSU blind area can be improved after the vehicle receiving the data exits the RSU range.
3. Self-organizing scheduling in RSU blind area
In order to better manage the vehicle nodes in the RSU blind area, effective data sharing is carried out, and the sharing target in the RSU blind area is completed. Self-organizing scheduling includes two parts: dynamic clustering mechanisms and data sharing mechanisms.
Dynamic clustering mechanisms better support data sharing by grouping vehicles with similar context information into the same cluster.
The data sharing mechanism broadcasts data items by selecting the vehicle node with the highest service capability in the cluster to provide service for the vehicle nodes traveling in opposite directions.
3.1 Dynamic clustering mechanism
In order to better manage the vehicle, and to reduce the duplication and redundancy of data generated during transmission, the method proposes link similarity (degree of link similarity,DLS) The concept of the present invention,DLSdependent on the duration of the link between vehiclesLDTPlease and pleaseSimilarity determinationA。
Vehicle link durationLDTIs an important reference value in a clustering algorithm, and the calculation method comprises the following steps:
wherein, LDT i j, vehicle node in RSU blind areaV i And vehicle nodeV j The duration of the vehicle link between, wherein,S i j, representing vehicle nodesV i And vehicle nodeV j A speed difference between them.
The request similarity indicates the degree to which the requests are identical between vehicles, and is defined as:
wherein, A i j, vehicle node in RSU blind areaV i And vehicle nodeV j Request similarity between.
Vehicle nodeV i And vehicle nodeV j The calculation mode of the link similarity between the links is as follows:
the greater the link similarity between vehicles, the higher the link similarity between nodes, i.e. the similar data request and motion state, such as short distance and similar speed, can keep better communication quality, so the greater the probability of being separated into the same cluster.
Vehicle nodeN i Average link similarity to neighboring vehicles within communication range:
Wherein, n i for nodes in RSU blind area and vehicleV i The number of adjacent vehicle nodes. Larger sizeThere will be an opportunity to become a cluster head.
Cluster generation:
an initialization stage, in which the vehicles do not belong to any cluster, each vehicle calculates each neighbor according to the collected context informationAnd establishing a neighbor linked list as an index of the competitive cluster head. By comparing itself with neighbors->Is determined to be a cluster head or a common cluster member, if the nodeN i Without any neighbor nodes or +.>Greater than all of its neighbors, then the nodeN i For a cluster head, non-cluster head members select a cluster with the greatest link similarity among their neighbors to join. A specific flow is shown in fig. 5.
Cluster maintenance:
after clustering is completed according to a clustering algorithm based on link similarity, the motion characteristics of cluster members basically cannot change in a large scale. Therefore, the vehicle node selected as the cluster head maintains the position of the cluster head of the vehicle node, and the non-cluster head node dynamically exits and joins the cluster according to the situation. Thus, although the cluster head nodes are fixed, the clusters are dynamically changed, and the stability of the clusters is ensured to a great extent. That is, frequent updating of the cluster head is reduced by sacrificing the optimal cluster head. The member node judges whether to perform a cluster maintenance mechanism according to the periodically acquired beacon data, and the cluster maintenance mechanism is executed in the following two cases:
1) Common members of clustersV j And cluster headCH k Is beyond the V2V communication rangeThenV j Exiting the current cluster and attempting to join the remaining clusters around; if there is no cluster around, then a cluster is generated by itself as a cluster head and its role in the cluster and new cluster ID are broadcast by control messages.
2) After cluster generation, a threshold is set in order to avoid frequent cluster switching by cluster membersλAnd judging whether the condition of switching clusters is reached. If there are other cluster heads nearby and with the cluster headDLSThe value is higher than the current cluster head and between themDLSThe difference is greater thanλAnd performing cluster switching. A specific flow is shown in fig. 6.
3.2 data sharing mechanism
After cluster generation, the BS calculates service capacity of each vehicle according to the cluster information and the vehicle context information, and selects clustersC k Vehicle node in (a)V i And will be in communication with the vehicle nodeV i Clusters running in opposite directions are stored in a collectionFor->Cluster->UsingRepresenting the requested data set in the cluster;β m is->Uses +.>Representation ofβ m According to the amount of data requestedα(V i ) And->Computing a vehicleV i Is to be used for the service capability of:
wherein, SC(V i ) Representing vehicle nodesV i I.e. the maximum number of data items that a vehicle node in a cluster can transmit;
By selecting the vehicle with the greatest service capability as the sender vehicle, the corresponding data item is broadcast for cluster service traveling in opposite directions when meeting the opposite cluster.
According to the self-organizing scheduling algorithm described above, vehicles with similar movement characteristics and data requests can be grouped into the same cluster, which can be managed conveniently. Meanwhile, vehicles with the maximum service capacity are selected from the clusters to send the same or similar data to the whole clusters at one time, so that the phenomenon that the same data are independently transmitted for multiple times is avoided, the repetition and redundancy of data transmission are reduced, and the efficiency of data sharing is improved.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.

Claims (10)

1. The data scheduling method based on the conflict graph and the clustering in the car networking environment is characterized by comprising the following operation steps of:
s1, acquiring digital information data in an experimental area;
s2, establishing a conflict graph of the related RSU node and the vehicle node through centralized scheduling in the coverage area of the RSU, and carrying out digital information data transmission according to a data transmission mode in the conflict graph;
S3, establishing clusters associated with all vehicle nodes through self-organizing scheduling synchronously carried out with centralized scheduling in an RSU blind area, and sending data for the vehicle nodes in the clusters which run in opposite directions through the vehicle nodes in the clusters.
2. The data scheduling method based on conflict graphs and clusters in the internet of vehicles environment according to claim 1, wherein the specific steps of step S1 are as follows:
s11, selecting a road with a set length as an experimental area;
s12, installing a base station in an experimental area, collecting and processing digital information data in real time by the base station through V2C communication, and storing the digital information data in a database;
s13, sequentially deploying RSUs along roads as RSU nodes, and connecting the RSUs with a base station through a wired link to obtain real-time digital information data from the base station; taking the digital information data as a data source, and serving vehicle nodes in the coverage area of the RSU node through V2I communication;
s14, determining the number of RSU nodes in the experimental area, and storing each RSU node in an RSU node setRIn the process, R={R 1 ,…,R i ,…,R n }，R 1 representing the 1 st RSU node in the experimental area,R i representing the first of the experimental zoneiThe number of RSU nodes is one,R n representing the first of the experimental zonenA plurality of RSU nodes;
S15, determining the number of vehicle nodes in the experimental area, and storing each vehicle node in a vehicle node setVIn the process, V={V 1 ,…,V i ,…,V m }，V 1 representing the 1 st vehicle node in the experimental area,V i representing the first of the experimental zoneiThe number of vehicle nodes in the vehicle is,V m representing the first of the experimental zonemA plurality of vehicle nodes;
s16, storing the RSU nodes and the vehicle nodes in the test area in the total node set in sequenceNIn the process, N={N 1 ,…,N i ,…,N j ,…,N m+n }，N=R∪V，N 1 representing the 1 st node in the experimental area,N i representing the first of the experimental zoneiThe number of nodes in the network is,N j representing the first of the experimental zonejThe number of nodes in the network is,N m+n representing the first of the experimental zonem+nA plurality of nodes;
s17, equally dividing digital information data in the database into subDThe I term, each part of size isd size And sequentially stored in a data setDIn the process, D={d 1 ,…,d i ,…,d |D| }，d 1 representing a datasetDIn the item 1 of the data,d i representing a datasetDThe first of (3)iThe data of the item(s),d |D| representing a datasetDOf the first part of the seriesDData of the I item; nodeN i The cached data item set formed by the cached digital information data isα(N i ) The method comprises the steps of carrying out a first treatment on the surface of the NodeN i The requested data item set composed of the requested digital information data isβ(N i ) The method comprises the steps of carrying out a first treatment on the surface of the And nodeN i Neighbor set of adjacent nodes isΩ(N i )={N j |d i j, ≤d v2v ,N j ∈NAnd } wherein,d i j, representing nodesN i Sum nodeN j The communication distance between the two-way communication device and the base station,d v2v representing V2V communication distance.
3. The data scheduling method based on conflict graph and cluster in the internet of vehicles environment according to claim 2, wherein when the vehicle node enters the coverage area of the RSU node, V2I communication can be performed with the RSU node or V2V communication can be performed with the neighboring vehicle node, so as to obtain the required digital information data; such a process of transmitting data by V2I or V2V communication Called asPT，PTThe expression is as follows:
wherein (1)>Representing nodesN i A kind of electronic devicePT；Representing nodesN i A set of transmitted data items constituted by the transmitted digital information data;Is thatIs a triplet of (3);Representing a receiving nodeN i A received data item set formed by the digital information data received by the vehicle node of the transmitted digital information data;
RSU nodeR i All within a coverage areaPTThe formed candidate scheduling set is，，Representing RSU nodesR i 1 st in coverage areaPT，Representing RSU nodesR i Within the coverage areaωPersonal (S)PT，Representing RSU nodesR i Within coverage area->Personal (S)PT；
Under the condition of meeting communication constraint, RSU node is selected through centralized schedulingR i The candidate scheduling set isNot interfere with each otherPTConstitutes a centralized scheduling set->，The expression is as follows:
wherein (1)>Representing RSU nodesR i One time in coveragePTA total number of valid data items that all receiving nodes can receive,I(. Cndot.) is shown at this timePTAnd the influence on data scheduling in the RSU blind area.
4. The data scheduling method based on conflict graph and cluster in the internet of vehicles environment according to claim 3, wherein the specific process of centralized scheduling in the coverage area of the RSU is as follows:
S2A1, a base station obtains context information of each node, wherein the context information comprises signal-to-noise ratio of the node; the signal-to-noise ratio is used for obtaining the channel quality capacity among the nodes, and the calculation formula of the channel quality capacity is as follows:
Wherein, C i j, representing nodesN i Sum nodeN j The capacity of the channel quality in between,SINR i j, representing nodesN i Sum nodeN j Signal to noise ratio between;
S2A2, then calculating the scheduling period in the experimental regionTThe maximum data item number which can be transmitted between any two nodes is calculated as follows:
wherein, η i j, representing nodesN i Sum nodeN j Between scheduling periodsTThe maximum number of data items that can be transmitted;
S2A3, constructing an undirected graph according to the context information of each node obtained by the base stationUG(N,E UG ) Undirected graphUG(N,E UG ) Two adjacent nodes are connected with each other through a transmission link;
S2A4, judging whether the transmission link is effective according to a judging criterion, and calculating the number of maximum data items which can be actually transmitted between two nodes in the effective transmission link, wherein the calculation formula is as follows:
wherein, lambda i j, Representing nodesN i To the nodeN j The maximum number of data items that can actually be transmitted by the transmission link of (a) isα(N i ) I represents a nodeN i The number of cached data items;
judgment criteria: if the number of data items owned by a sender node for sending digital information data in a transmission link is smaller than the maximum number of data items which can be transmitted between two nodes of the transmission link, or the digital information data cannot be transmitted between the two nodes, the transmission link is invalid, otherwise, the transmission link is valid;
S2A5 according to undirected graphUG(N,E UG ) In the effective transmission link and the transmission direction of the effective transmission link, the undirected graphUG(N,E UG ) Conversion to a directed graphDG(N,E DG )；
S2A6, on the premise of meeting communication constraint, mapping the directed graphDG(N,E DG ) Conversion to conflict graphG I And calculating effective data actually received by the receiver node, and storing the effective data in an effective data set, wherein the calculation formula of the effective data set is as follows:
wherein (1)>Representing nodesN i Send->Giving nodesN j When the nodeN j A set of valid data actually received;
S2A7, then calculatePTIs used for the weight of the (c),PTthe weight of (1) comprises a quantity weight and an influence weight on an RSU blind area, and the calculation formula of the quantity weight is as follows:
the calculation formula of the influence weight is as follows:
PTthe weights of (2) are calculated as follows:
wherein (1)>Representation and vehicle nodeV j A set of vehicle nodes traveling in opposite directions;V S is->Middle (f)SA plurality of vehicle nodes;Representing vehicle nodesV S A requested collection of data items;U i representing the first in the conflict graphiA plurality of nodes;W(U i ) Representing nodesU i Is a weight of (2).
5. The data scheduling method based on conflict graph and cluster in the internet of vehicles environment according to claim 4, wherein the directed graph isDG(N,E DG ) Conversion to conflict graphG I The steps of (a) are as follows:
S2B1, firstly calculating each through a judgment criterionPTEach element in the triplet of (2);
judgment criterion one:i.e. nodesN i The transmitted data belonging to a nodeN i Buffering data in a set of data items;
judgment criterion II:，representing nodesN i The number of data items in the set of transmitted data items constituted by the transmitted digital information data,Ω(N i ,DG) Representation belongs to a directed graphDG(N,E DG ) Middle nodeN i Neighbor sets, i.e. nodesN i The number of data items transmitted belongs to the directed graphDG(N,E DG ) Middle nodeN i Any one of the neighbor edge weights;
S2B2, then calculateAnd pass->Calculate->，The calculation formula of (2) is as follows:
the calculation formula of (2) is as follows:
wherein, Ω(N i ,DG) Representation belongs to a directed graphDG(N,E DG ) Middle nodeN i Is a neighbor set of (a);
S2B3 due to differencesPTMutual interference exists between the two communication nodes, so that collision is caused, and therefore, communication constraint for eliminating the collision is set to avoid the occurrence of the collision, and the communication constraint is as follows:
constraint one: same scheduling periodTIn the inner part of the inner part,the same node cannot simultaneously transmit and receive data;
constraint II: same scheduling periodTEach node can only transmit one group of data items at a time;
constraint three: same scheduling periodTIn the method, the same node cannot simultaneously receive data sent by a plurality of nodes;
S2B4, according to communication constraint, conflict exists between any twoPTAdding an edge between nodes to represent that transmission conflicts exist; traversing all conflicts in RSU coveragePTNodes and corresponding edges are drawn to form a conflict graphG I 。
6. The data scheduling method based on conflict graph and cluster in the internet of vehicles environment according to claim 5, wherein after calculation is completedPTAfter the weights of (2), solving the maximum weighted independent set by using a marking algorithm, wherein the specific steps are as follows:
S2C1, initializing a conflict graph, and marking all nodes as unaccessed;
S2C2, calculating each nodeW(U i )/(d(U i )+1) A value of whereind(U i ) Representative nodeU i Degree of (3);
S2C3 selection from non-accessed nodesW(U i ) Adding the largest node into the initial independent set, and marking the newly added node and the adjacent nodes as accessed nodes;
S2C4, repeating the step S2C3 until all nodes are marked as accessed;
S2C5, enabling the initial independent set to be the maximum weighted independent set, and determining a sending node, a sent data set and a receiving node to share data according to each node in the maximum weighted independent set.
7. The data scheduling method based on conflict graph and clustering in the car networking environment according to claim 6, wherein the clustering algorithm is adopted to build clusters, and the cluster building process is as follows:
S31, acquiring and vehicle nodeV i Neighbor set formed by adjacent vehicle nodes, wherein the neighbor set isΩ(V i )={V j |d i j, ≤d v2v ,V j ∈VIf (3)Ω(V i ) Empty set, then vehicle nodeV i As a cluster head; otherwise, go to step S32;
s32, calculating a non-empty setΩ(V i ) Average link similarity of each vehicle node in (a) if the vehicle nodeV i If the average link similarity of the (a) is maximum, the vehicle node is determined to beV i As a cluster head; otherwise, step S33 is entered;
the average link similarity calculation formula is as follows:
wherein (1)>Indicating the first place in the RSU blind areaiAverage link similarity of adjacent vehicle nodes in the communication range of each vehicle node;n i for nodes in RSU blind area and vehicleV i The number of adjacent vehicle nodes;DLS i j, vehicle node in RSU blind areaV i And vehicle nodeV j Link similarity between the two;DLS i j, vehicle node in RSU blind areaV i And vehicle nodeV j Link similarity between the two;β(V i ) Vehicle node in RSU blind areaV i A request data item set formed by the requested digital information data;β(V i ) Vehicle node in RSU blind areaV i A request data item set formed by the requested digital information data;A i j, vehicle node in RSU blind areaV i And vehicle nodeV j Request similarity between;LDT i j, vehicle node in RSU blind areaV i And vehicle node V j A vehicle link duration therebetween;S i j, representing vehicle nodesV i And vehicle nodeV j A speed difference therebetween;
s33, selecting a non-empty setΩ(V i ) The average link similarity is greater than the vehicle nodeV i And store the node setsMIn (a) and (b);
s34, judging node setMIf there is cluster head in the network, if there is cluster head, then vehicle nodeV i Adding the components with the maximum valueDLSCluster in which cluster head of value is located; conversely, vehicle nodeV i As a cluster head.
8. The data scheduling method based on the conflict graph and the clustering in the internet of vehicles according to claim 7, wherein after the clustering algorithm of the vehicle nodes based on the link similarity finishes clustering in the RSU blind area, the motion characteristics of the cluster members remain unchanged, and the vehicle nodes selected as the cluster heads maintain their own cluster head positions; the non-cluster head node dynamically exits and joins the cluster according to the situation, and judges whether a cluster maintenance mechanism is to be carried out or not according to the periodically obtained beacon data; the cluster maintenance mechanism is performed in two cases:
first case: when common members of a clusterV j And cluster headCH k Is beyond the V2V communication range,V j exiting the current cluster and attempting to join other clusters around; if there are no clusters around, then the general member V j Generating a cluster by oneself as a cluster head;
second case: after cluster generation, a threshold is setλThe method comprises the steps of carrying out a first treatment on the surface of the If common members of a clusterV j Other cluster heads exist nearby and are commonGeneral memberV j With the other cluster headDLSA value greater thanV j With the current cluster headDLSValue of two at the same timeDLSThe difference between the values is greater thanλ，Then cluster switching is performed; otherwise, cluster switching is not performed.
9. The data scheduling method based on conflict graph and clustering in the internet of vehicles environment according to claim 8, wherein after the clusters are generated, the service capacity of each vehicle node in the clusters is calculated, and the calculation process is as follows:
selecting clustersC k Vehicle node in (a)V i And will be in communication with the vehicle nodeV i Clusters running in opposite directions are stored in a collectionFor->Cluster->Use->Representing the requested data set in the cluster;β m is->One of the requests, useRepresentation ofβ m According to the amount of data requestedα(V i ) And->Computing vehicle nodesV i Is to be used for the service capability of:
wherein, SC(V i ) Representing vehicle nodesV i I.e. the maximum number of data items that a vehicle node in a cluster can transmit;
the vehicle node with the largest service capability is selected as a sender node for sending data, and corresponding data items are broadcasted to serve the clusters running in opposite directions when meeting the clusters running in opposite directions.
10. The data scheduling method based on conflict graph and clustering in the internet of vehicles environment according to claim 9, wherein the data transmission mode in the experimental area comprises centralized scheduling and self-organizing scheduling, the centralized scheduling and self-organizing scheduling form a centralized and self-organizing collaborative scheduling problem, and the overall objective of the centralized and self-organizing collaborative scheduling problem is represented as follows:
wherein, Urepresenting the maximum number of data items that can be transmitted in the experimental area;Representing clustersC k The number of data items transmitted by the vehicle node having the greatest service capability.
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