CN103987103B - A kind of vehicle self-organizing network route selection method based on game theory - Google Patents
A kind of vehicle self-organizing network route selection method based on game theory Download PDFInfo
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Abstract
The present invention discloses a kind of vehicle self-organizing network route selection method.It is related to communication technical field, the source vehicle for intending being communicated checks whether communication objective node is one hop neighbor node, if so, then sending packet, otherwise, sends route request information to Router Management Center.Router Management Center determines SV candidate relay vehicle, and it is betting model to model SV routing problems, models SV and RV gain and loss function, by solving betting model optimization solution, it may be determined that SV optimizes routing scheme.This method comprehensive assessment influences many factors of route transmission characteristic, and the combined optimization based on optimization SV and RV incomes realizes SV best route selection, can effective guarantee user QoS, realize that overall system performance optimizes.
Description
Technical field
The present invention relates to the routing technology of wireless communication field, particularly vehicle self-organizing network (VANET).
Background technology
With the fast development of mobile communication and network technology, vehicle self-organizing network (Vehicular Ad-hoc
NETwork, VANET) it is used as the important set of intelligent transportation system (Intelligent Transportation System, ITS)
Into partly receiving significant attention in recent years.VANET is a kind of self-organizing, the inter-vehicular communication network of structure opening, using the teaching of the invention it is possible to provide
Communication between vehicle and between vehicle and roadside infrastructure.VANET combining global positioning systems (GPS) and radio communication
Technology, such as WLAN (WLAN), cellular network, the data that high-speed is provided for the vehicle in high-speed moving state connect
Enter service, and support the information exchange between vehicle, it has also become support vehicles driving safety, the communication of vehicle high-speed data is provided,
Realize the effective technology of intelligent transportation system.
In VANET, if the communication objective vehicle (DV) of source vehicle (SV) is located at beyond a SV jump coverage, it can be based on
Specific route selection algorithm, one or more relay vehicles (RV) are selected to forward packet to DV for SV.However, car in VANET
Mobility cause the quick change of network topology structure, wireless channel decline and multi-user's competitive channel cause signal to pass
Defeated limited performance, and the characteristic such as each candidate RV performance difference propose new be stranded to the routing technology in VANET
Difficult and challenge.In the case where multiple candidate RV be present, physical channel characteristics, chain circuit message collision how are considered, RV's
The many factors such as mobility and transmission characteristic, Optimization route is selected to ensure user's communication requirement, and realize system function optimization,
VANET important subject is turned into, there is important scientific research and engineer applied meaning.
Document [is based on multipath Lifetime and trust in Chen Chen, Jiao Xiaohui, Du Xiaobo, Pei Qingqi, Jin Yanan, VANET
The instant Route Selection of degree, publication number CN102916889A, publication date 2013 year 2 month 6] propose to be based in a kind of VANET
The instant route selection method of multipath Lifetime and degree of belief, for city vehicle network service.This method selects path
Mulitpath of the Lifetime within threshold values alternately path, then depend from selecting degree of belief highest path to carry out data
Transmission.Document [Yu Rong, thanks triumph, Fan Di, Xia Wenlong, a kind of cooperative information transmission method towards car networking, publication number
CN103167024A, June 19 2013 publication date] propose a kind of cooperative information transmission method towards car networking, source section
Point inquiry roadside unit (RSU) obtain destination node neighbours board units (OBU) information, then according to selection meet it is specific away from
From desired multiple destination node neighbours OBU as cooperating relay, to realize reliable information transfer.
Document [Mahmoud Hashem Eiza, Qiang Ni, An Evolving Graph-Based Reliable
Routing Scheme for VANETs, IEEE Transactions on Vehicular Technology, Vol.62,
No.4, MAY2013, pp.1493-1504] routing mechanism based on evolution graph model is proposed, obtained by using evolution diagram
The topology structure evolution characteristic of VANET networks is taken, so as to predefine reliable routing.Document [Junichiro
Fukuyama,Sunnyvale,C A,Probabilistic Routing for Vehicular Ad Hoc Network,
Patent No.US7885285B2,Issued Date:Feb.8,2011] propose a kind of VANET Route Selections based on probability
Algorithm, communication probability highest path is selected as destination path.
The existing research for VANET route selection algorithms was mainly considered based on node communication distance, link duration
And the factor such as link communication probability is routed, Consideration is more single, fails the comprehensive physical characteristic of channel, link disappears
Breath collision, RV mobility and transmission characteristic etc. are multifactor, in addition, in optimum choice cooperating relay, generally only consider SV's
Performance optimizes, and has not been able to consider comprehensively RV transmission demand, stable state transmission characteristic and the income etc. for providing relay forwarding business
Factor, RV communication performances may be caused can not to ensure and overall performance of network critical constraints.
The content of the invention
To solve the above-mentioned problems in the prior art, the present invention proposes a kind of VANET route choosings based on game theory
Selection method, it is comprehensive by establishing betting model between SV and relay vehicle (RV) under the scene that multiple source vehicles (SV) be present
Consider SV and RV income, realize optimization Route Selection.It the described method comprises the following steps：
Source vehicle SV checks whether communication objective node DV is one hop neighbor node, if so, then sending packet to DV；
Otherwise, route request information is sent to Router Management Center RMC, and RMC determines SV candidate relay vehicle RV, and is based on game theory
Route selection method determine each SV optimal RV, and send route confirmation message RACK, Route Selection notified to each SV and RV
As a result；After SV receives RACK, communicated with corresponding RV.
Route selection method based on game theory determines that each SV optimal RV is specifically included：The receipts obtained according to forwarding data
Revenue function, the cost function of benefit foundation determine gain and loss function, are specially：Assuming that there is M SV and N number of RV in network, according to i-th
The income that individual source vehicle SV_i selection j-th candidates relay vehicle RV_j forward data to obtain for itSV_i select RV_j for
It forwards the cost paid needed for dataCall formula：(1≤i≤M, 1≤j≤N) calculates SV's
Gain and loss function isIf the route requests that RV_j receives SV_i forward data for it, receive SV_i route requests according to RV_j
And the income of data acquisition is forwarded for itThe cost that RV_j is paid by SV_i forwardings dataCall formula：(1≤i≤M, 1≤j≤N) calculates RV gain and loss functionData forwarding is selected according to gain and loss function
Optimal path.Router Management Center RMC determines SV candidate RV according to SV and DV positional information, ifOrThen RV SV for this candidate RV, if without the time for meeting to require
RV is selected, then selects the vehicle that distance SV is nearest in SV neighbours' vehicle to forward packet as relay vehicle for it, wherein, SV_i
Position beIts corresponding DV position isRV_j position isBy in certain period of history T,
RV_j sends and receives the total N of packetj, the size S of each packetB, according to formula：Determine RV_j's
History bandwidth, according to formula：Establish revenue function and determine incomeWherein, αi
Represent the revenue factor of SV_i unit speed, Ti,jRepresent that SV_i selections RV_j carries out data transmission period needed for data forwarding,
βi,jThe credit factor between SV_i and RV_j is represented,For constant, the slope of curve of SV_i revenue functions is corresponded to respectively
And Ti,jDeviant,Represent the collision probability of RV_j packet；The unit speed Price factor for intending paying according to SV_i
γi, according to formula：Determine cost functionWherein, Ri,jRepresent the link transmission between SV_i and RV_j
Speed.Assuming that M≤N, supplements N-M virtual vehicle, according to formulaCalculate SV and RV
Joint value of utility, wherein, ρi,j∈{0,1}, According to SV_i and RV_
The Successful transmissions probability of link between jCall formulaIt is the income that SV_i forwards data to obtain to calculate RV_j,
Wherein,Represent RV_j occupied bandwidthsThe number of data packets of Successful transmissions, according to formula：
The cost that RV_j is paid by SV_i forwardings data is calculated, wherein,For constant, respectively homologous thread slope andDeviant, cjRepresent RV_j unit resource efficiency factor.The determination of the data packet collision probability is further wrapped
Include：According to formula：Data packet collision probability is calculated, wherein, mjFor RV_j surrounding neighbours vehicles
Number, τjFor the packet average arrival rate of the RV in the unit time.The rate travel for setting SV_i is that average isVariance isNormally distributed random variable, the rate travel for setting RV_j is that average isVariance isNormal distribution
Stochastic variable, according to formula：Determine the credit factor between SV_i and RV_j
βi,j, wherein,Speed trust value between SV_i and RV_j, θi,jLine and SV_i between SV_i, RV_j and its
Angle between DV lines, di,jFor the distance between SV_i and RV_j, HiFor SV_i communication covered radius, 0≤λ1,λ2,λ3
≤ 1 is given constant weight.The optimal path for selecting data forwarding according to gain and loss function further comprises：Setting is had the right bipartite graph
G=(V1,V2, E), wherein, vertex set V1Represent SVs set, i.e. V1=[SV1,SV2,...,SVN], vertex set V2Represent RVs
Set, i.e. V2=[RV1,RV2,...,RVN]；Have the right bipartite graph G=(V1,V2, E) in side { SVi,RVjWeights on ∈ E (G)
Represent i-th of SV and j-th of RV gain and loss functional value；Bipartite graph G=(the V that have the right are solved using feasible the Vertex Labeling method1,V2,E)
Maximum matching weights, the path of maximum matching weights is SV and the optimal routes of RV.
Specifically further comprise：
(1) it is each SV and RV to determine game player, it is assumed that shared M SV and N number of RV；
(2) selection strategy is：It is its turn that i-th of SV (SV_i) (1≤i≤M), which selects j-th of RV (RV_j) (1≤j≤N),
Data are sent out, RV_j (1≤j≤N) receives or refusal SV_i (1≤i≤M) data forwarding request.
(3) gain and loss function：If SV_i selects RV_j to forward data for it, RV_j receives SV_i relay request, corresponding SV
Gain and loss function beRV gain and loss function isThe revenue function of the income foundation obtained according to forwarding data, cost
Function determines gain and loss function.
Establish SV gain and loss functionFor：(1≤i≤M, 1≤j≤N), wherein,Represent
SV_i selects the income that RV_j forwards data to obtain for it,For SV_i select RV_j for its forward data needed for pay into
This.Establish revenue functionFor：Wherein, αiRepresent the receipts of SV_i unit speed
The beneficial factor,RV_j history bandwidth is represented, by certain period of history T, the packet average transmission rate of the RV characterizes, i.e.,Wherein NjFor in T periods, the sum for the packet that RV_j sends and receives, SBFor the size of each packet.
Ti,jData transmission period needed for representing SV_i selection RV_j progress data forwardings, is represented byWherein SiRepresent
SV_i MAC data bag size, Ri,jThe link transmission rate between SV_i and RV_j is represented, Represent RV_j available bandwidth, SINRi,jRepresent RV_j Signal to Interference plus Noise Ratio.TBORepresent flat when packet transmits by RV_j
Equal back off time.βi,jThe credit factor between SV_i and RV_j is represented,For constant, respectively homologous thread slope and
Ti,jDeviant.The collision probability of RV_j packet is represented,Wherein, mjFor RV_j weeks
Enclose neighbours' vehicle number, τjFor the packet average arrival rate of the RV in the unit time, modeling cost functionForWherein γiRepresent that SV_i intends the unit speed Price factor paid.Model SV_i and RV_j between credit because
Sub- βi,jForWhereinSpeed trust value between SV_i and RV_j, θi,jFor
The angle between line and SV_i and its DV line between SV_i, RV_j, di,jFor the distance between SV_i and RV_j, HiFor SV_i
Communication covered radius, λ1、λ2、λ3For constant.Model the relative velocity between SV_i and RV_jWherein△vi,jProbability density function be：
The speed trust value modeled between SV_i and RV_j is △ vi,jLess than threshold speed vthProbability, i.e.,
If the route requests that RV_j receives SV_i forward data for it, the gain and loss function modelling of the RV is：(1≤i≤M, 1≤j≤N), wherein,Represent that RV_j receives SV_i route requests and forwards data to obtain for it
The income obtained, is modeled as：Wherein,The Successful transmissions probability of link, models SV_ between expression SV_i and RV_j
Channel model is Nakagami fading channels between i and RV_j, can be obtained The cost that RV_j is paid by SV_i forwardings data is represented, is modeled as：Wherein cjRepresent RV_
J unit resource efficiency factor,For constant, respectively homologous thread slope andDeviant.
Supplement | M-N | individual virtual vehicle, it is 0 to make its utility function value, M+N participant's game can be extended into 2max
(M, N) individual participant's game.Assuming that N >=M, it is combined utility matrix and is represented by：
Modeling SV and RV combines utility function：Wherein, optimized variable ρi,j
Meet：ρi,j∈{0,1},
(4) using Kuhn-Munkres algorithm optimizations SV and RV joint total utility function, it is comprised the following steps that：
Have the right bipartite graph G=(V1,V2, E) in vertex set V1Represent SVs set, i.e. V1=[SV1,SV2,...,
SVN], vertex set V2Represent RVs set, i.e. V2=[RV1,RV2,...,RVN]；Have the right bipartite graph G=(V1,V2, E) in side
{SVi,RVj∈ E (G) weights combine utility function value for SV_i and RV_j；RV selections based on joint gain and loss function optimization
Problem can correspond to the bipartite graph G=(V that have the right1,V2, E) matching problem；Using feasible the Vertex Labeling method, (Kuhn-Munkres is calculated
Method) solve the bipartite graph G=(V that have the right1,V2, E) and maximum weight matching problem, optimal routing strategy can be obtained.
The present invention, which considers, influences the multifactor of SV, RV communication performance, models SV and RV gain and loss functions, realizes optimization road
By selecting；By modeling and optimizing combine utility functions of the SV with RV, feasible system combination property is optimal.
1.1.1 brief description of the drawings
VANET path selection systems model in Fig. 1 present invention；
VANET Route Selection flow charts based on game theory in Fig. 2 present invention；
SV Route Selection flow chart in Fig. 3 VANET of the present invention.
1.1.2 embodiment
For the object, technical solutions and advantages of the present invention expression is more clearly understood, below in conjunction with the accompanying drawings to the present invention
It is described in further detail.
In the present invention, it is related to the M source vehicle (SV) for intending being communicated and purpose is forwarded information to by relay vehicle (RV)
Vehicle.One is carried out to all SV at Router Management Center (RMC) place and jumps Route Selection, the selection strategy can be extended to multihop routing
Scene.
Application scenarios of the present invention, repeated vehicle transfers data to respective purpose vehicle respectively by source vehicle SV1 and SV2
DV1 and DV2.Present invention can apply to the scene that multiple SV perform data forwarding.
Fig. 1 is VANET path selection system models in the present invention, it is assumed that SV and RV number is respectively M and N, each SV
A RV can only be at most selected to forward data for it, each RV can only at most select a SV to forward data for it.
The source vehicle (SV) for intending being communicated checks whether communication objective node (DV) is one hop neighbor node, if so, then
Packet is sent to DV, otherwise, sends route request information (RReq) to Router Management Center (RMC).Include and disappear in RReq message
Cease the unit that type, the SV lowest-bandwidth demand for identifying ID_DV, SV for identifying ID_SV, DV, revenue factor and its plan are paid
Speed Price factor.After RMC receives the RReq message from SV, SV candidate RV is determined according to SV and DV position.Assuming that SV_i
Position isIts DV position isRV_j position isIfOrThen RV SV for this candidate RV.It is if nearest without the candidate RV for meeting to require, chosen distance SV
Neighbours' vehicle as RV forward packet.RMC performs the SV route selection algorithms based on theory of games, determines SV route choosing
Strategy is selected, and sends route confirmation message RACK, routing select result is notified to each SV and RV.Message class is included in RACK message
Type, SV mark ID_SV, RV mark ID_RV and DV mark ID_DV.After SV receives RACK, communicated with corresponding RV.
RMC performs the SV route selection algorithms based on theory of games and specifically included：
Fig. 2 is the VANET Route Selection flow charts disclosed by the invention based on game theory, is specifically included：
201：Establish game player.Game player is SV and RV, it is assumed that shared M SV and N number of RV.
202：Establish player's strategy.Strategy is selected by player：SV selects j-th of (1≤j≤N) RV to be forwarded for it
Data, are designated as RV_j, and RV receives i-th of (1≤i≤M) SV route requests and forwards data for it.
203：Model player's utility function.
SV utility function and RV utility function are calculated respectively, if SV_i selects RV_j to forward data, SV effect for it
It is with function modelling：(1≤i≤M, 1≤j≤N), if RV_j receives SV_i route requests and for its turn
Data are sent out, the utility function of the RV is modeled as：(1≤i≤M, 1≤j≤N).Represent respectively
SV_i selects the cost subfunction that RV_j need to pay for the income subfunction and SV of its forwarding data acquisition,Represent the RV_j
Receive SV_i route requests and the income subfunction for forwarding data to obtain for it,Represent that RV_j is propped up by SV_i forwardings data
The cost subfunction paid.
204：Utility function subfunction is modeled respectively：
Model SV_i income subfunctionFor：Wherein, αiRepresent that SV_i is mono-
The revenue factor of bit rate,RV_j history bandwidth is represented, by certain period of history T, the packet average transmission of the RV is fast
Rate characterizes, i.e.,Wherein NjFor in T periods, the sum for the packet that RV_j sends and receives, SBFor each number
According to the size of bag.Ti,jData transmission period needed for representing SV_i selection RV_j progress data forwardings, is represented byWherein SiRepresent SV_i MAC data bag size, Ri,jRepresent the link transmission speed between SV_i and RV_j
Rate, Represent RV_j available bandwidth, SINRi,jRepresent RV_j Signal to Interference plus Noise Ratio.TBOTable
Show packet by average backing off time during RV_j transmission.βi,jThe credit factor between SV_i and RV_j is represented,
For constant, difference homologous thread slope and Ti,jDeviant.The collision probability of RV_j packet is represented,Wherein, mjFor RV_j surrounding neighbours vehicle numbers, τjPacket for the RV in the unit time is put down
Equal arrival rate.Model the credit factor-beta between SV_i and RV_ji,jForWhereinFor
Speed trust value between SV_i and RV_j, θi,jThe folder between line and SV_i and its DV line between SV_i, RV_j
Angle, di,jFor the distance between SV_i and RV_j, HiFor SV_i communication covered radius, λ1、λ2、λ3For constant.Model SV_i with
Relative velocity between RV_jWherein
△vi,jProbability density function be：Model the speed trust value between SV_i and RV_j
For △ vi,jLess than threshold speed vthProbability, i.e.,Modeling SV_i cost function beWherein γiRepresent that SV_i intends the unit speed Price factor paid.
Model RV_j income subfunctionWherein,The success of link between expression SV_i and RV_j
Transmission probability, channel model is Nakagami fading channels between modeling SV_i and RV_j, can be obtained
Establish RV_j cost subfunctionWherein cjRepresent RV_j unit resource efficiency because
Son,For constant, respectively homologous thread slope andDeviant.
205：Virtual vehicle is supplemented, M+N participant's game is extended to 2max (M, N) participant's game.
Supplement | M-N | individual virtual vehicle, it is 0 to make its utility function value, M+N participant's game can be extended into 2max
(M, N) individual participant's game.Assuming that N >=M, it is combined utility matrix and is represented by：
206：SV and RV joint effectiveness is：Wherein, optimized variable ρi,jMeet：ρi,j
∈{0,1},
207:Betting model is solved based on Kuhn-Munkres algorithm optimizations.
(1) have the right bipartite graph G=(V1,V2, E) in vertex set V1Represent SVs set, i.e. V1=[SV1,SV2,...,
SVN], vertex set V2Represent RVs set, i.e. V2=[RV1,RV2,...,RVN]。
(2) have the right bipartite graph G=(V1,V2, E) in side { SVi,RVjWeights on ∈ E (G) represent i-th of SV and j-th
RV joint value of utility.
(3) the RV select permeabilities based on gain and loss function optimization can correspond to the bipartite graph G=(V that have the right1,V2, E) matching ask
Topic.
(4) the bipartite graph G=(V that have the right are solved using feasible the Vertex Labeling method (Kuhn-Munkres algorithms)1,V2, E) power
It is worth maximum matching problem, SV and the optimal routing strategies of RV can be obtained.
208：Perform optimisation strategy.
RMC is based on allocative decision and sends route assignment message RACK to each SV, notifies making routing decisions result.
Fig. 3 show the Route Selection flow chart of SV in VANET of the present invention.
301：Certain SV intends forwarding information to purpose vehicle DV；
302：The SV judges whether target vehicle is neighbours' vehicle.If so, step 410 is then gone to, if it is not, then going to step
403；
303：SV sends route request information RReq to RMC.RReq message includes type of message, SV mark ID_SV, DV
Mark ID_DV, SV lowest-bandwidth demand, revenue factor and intend the unit speed Price factor paid；
304：RMC determines SV candidate relay vehicle.Assuming that SV_i positions areRV_j positions are
SV_i DV position isIfOrThen the RV is this
SV candidate RV.If the nearest vehicles of a distance SV are selected to make in its adjacent vehicle without the candidate RV, SV for meeting to require
Packet is forwarded for RV.
305：RMC is based on game theory modeling SV Route Selection models, determines routing scheme.
Relay selection problem is following betting model between SV and RV：
1. game player is SV and RV, it is assumed that shared M SV and N number of RV；
2. strategy is selected by player：SV selects j-th of (1≤j≤N) RV to forward data for it, is designated as RV_j, RV connects
Data are forwarded by i-th of (1≤i≤M) SV route requests and for it.
3. gain and loss function：SV_i select RV_j for its forward data utility function beRV_j receives SV_i routes please
Ask, data are forwarded for it, can be according to utility functionRMC is based on game theory modeling route assignment problem, and uses and have the right most
Excellent matching algorithm seeks optimal solution, it is determined that optimization route assignment scheme.
306：RMC sends RACK message to SVs.
RMC is based on allocative decision and sends route assignment message RACK to each SV, notifies making routing decisions result, and RACK disappears
Breath includes the mark ID_RV and DV of mark ID_SV, RV comprising type of message, SV mark ID_DV.
307：SVs sends packet to corresponding RVs.
308：RV judges whether it is the hop neighbor for corresponding to DV.If so, then going to step 410, otherwise, step is gone to
409。
309：Note RV is new SV, goes to step 404.
310：RV sends data to DV.
Claims (4)
- A kind of 1. vehicle self-organizing network route selection method based on game theory, it is characterised in that：Source vehicle SV checks communication Whether destination node DV is one hop neighbor node, if so, then sending packet to DV；Otherwise, route request information is sent extremely Router Management Center RMC, RMC determines SV candidate relay vehicle RV, and the route selection method based on game theory determines each SV Optimal RV, and send route confirmation message RACK, notify routing select result to each SV and RV, specifically include, routing management Center RMC determines SV candidate RV according to SV and DV positional information, ifOrThen RV SV for this candidate RV, if without the candidate RV for meeting to require, selection SV neighbours' car Vehicle nearest distance SV forwards packet as relay vehicle for it in, wherein, SV_i position isIts is right The position for answering DV isRV_j position isAccording to the Successful transmissions probability of link between SV_i and RV_jCall formulaIt is the income that SV_i forwards data to obtain to calculate RV_j, according to formula：The cost that RV_j is paid by SV_i forwardings data is calculated, wherein,Represent that RV_j takes BandwidthThe number of data packets of Successful transmissions,For constant, respectively homologous thread slope andDeviant, cj Represent RV_j unit resource efficiency factor, γiThe unit speed Price factor for intending paying for SV_i；By in certain period of history T, RV_j sends and receives the total N of packetj, the size S of each packetB, according to formula：Determine RV_j History bandwidth, according to formula：Establish revenue function and determine incomeWherein, αiRepresent the revenue factor of SV_i unit speed, Ti,jWhen representing that SV_i selections RV_j carries out data transfer needed for data forwarding Between, βi,jThe credit factor between SV_i and RV_j is represented, For constant, the curve for corresponding to SV_i revenue functions respectively is oblique Rate and Ti,jDeviant,Represent the collision probability of RV_j packet；The unit speed Price factor for intending paying according to SV_i γi, according to formula：Determine cost functionWherein, Ri,jRepresent the link transmission between SV_i and RV_j Speed；Revenue function, the cost function that the income obtained according to forwarding data is established determine gain and loss function, are specially：Assuming that net There is M SV and N number of RV in network, select j-th candidates relay vehicle RV_j to forward data to obtain for it according to i-th of source vehicle SV_i The income obtainedSV_i selects RV_j to forward the cost paid needed for data for itCall formula： (1≤i≤M, 1≤j≤N) calculate SV gain and loss function beIf the route requests that RV_j receives SV_i forward data for it, The income for receiving SV_i route requests according to RV_j and forwarding data to obtain for itRV_j is propped up by SV_i forwardings data The cost paidCall formula：(1≤i≤M, 1≤j≤N) calculates RV gain and loss functionAccording to Gain and loss function selects the optimal path of data forwarding；Set SV_i rate travel average beVariance isNormal state Distribution variables, the rate travel average for setting RV_j areVariance isNormally distributed random variable, according to Formula：Determine the credit factor-beta between SV_i and RV_ji,j, wherein,For Speed trust value between SV_i and RV_j, θi,jThe folder between line and SV_i and its DV line between SV_i, RV_j Angle, di,jFor the distance between SV_i and RV_j, HiFor SV_i communication covered radius, 0≤λ1,λ2,λ3≤ 1 is constant weight； After SV receives RACK, communicated with corresponding RV.
- 2. according to the method for claim 1, it is characterised in that：Assuming that M≤N, supplements N-M virtual vehicle, according to formulaSV and RV joint value of utilities are calculated, wherein, ρi,j∈{0,1},
- 3. according to the method for claim 1, it is characterised in that：The determination of the data packet collision probability further comprises： According to formula：Data packet collision probability is calculated, wherein, mjFor RV_j neighbours' vehicle numbers, τjFor list The packet average arrival rate of the RV_j in the time of position.
- 4. according to the method for claim 1, it is characterised in that the optimal path for selecting data forwarding according to gain and loss function enters One step includes：Setting is had the right bipartite graph G=(V1,V2, E), wherein, vertex set V1Represent SVs set, i.e. V1=[SV1, SV2,...,SVN], vertex set V2Represent RVs set, i.e. V2=[RV1,RV2,...,RVN]；Have the right bipartite graph G=(V1,V2, E side { SV in)i,RVjWeights on ∈ E (G) represent i-th of SV and j-th of RV gain and loss functional value；Using feasible the Vertex Labeling Method solves the bipartite graph G=(V that have the right1,V2, E) maximum matching weights, the path of maximum matching weights is SV and the optimal routes of RV.
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| CN104320789B (en) * | 2014-11-05 | 2017-11-03 | 安徽大学 | A kind of car networking RSU optimal configuration methods based on game theory |
| CN104320825A (en) * | 2014-11-20 | 2015-01-28 | 重庆邮电大学 | Ad hoc network route selection method based on repeated game |
| CN105530680B (en) * | 2015-12-22 | 2019-02-15 | 重庆邮电大学 | A kind of vehicle self-organizing network relay vehicle selection method |
| CN106131871B (en) * | 2016-07-21 | 2019-05-17 | 西北大学 | A kind of optimized data transmission method towards car networking |
| CN106658649A (en) * | 2016-10-14 | 2017-05-10 | 天津大学 | Information sharing method in wireless network with uncertain cooperative nodes |
| CN106792970B (en) * | 2017-02-17 | 2019-12-03 | 重庆邮电大学 | A kind of vehicle self-organizing network route selection method |
| CN108271139A (en) * | 2018-01-18 | 2018-07-10 | 重庆大学 | A kind of method for routing based on software definition car networking |
| CN108712768B (en) * | 2018-04-13 | 2020-06-19 | 西安交通大学 | Routing method based on mobility and MAC layer competitive access in Internet of vehicles |
| CN108572875B (en) * | 2018-04-28 | 2020-09-04 | 辽宁工程技术大学 | Resource allocation method, device and system |
| CN109831758B (en) * | 2019-03-19 | 2020-12-04 | 南京邮电大学 | Method for selecting content forwarding node in vehicle-mounted self-organizing network based on service type |
| CN111372219B (en) * | 2020-02-19 | 2022-04-12 | 重庆邮电大学 | Internet of vehicles link selection and resource allocation method |
| CN113163362A (en) * | 2021-02-02 | 2021-07-23 | 上海大学 | Data packet forwarding system and method based on vehicle formation |
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