CN103442389A - Switching method based on IEEE80211p in VANET - Google Patents

Abstract

The invention belongs to the technical field of mobile communication, and discloses a switching method based on IEEE80211p in a VANET. The method comprises the steps of firstly, only considering the RSSI of an RSU to decide whether switching is carried out or not, and dividing the switching into hard switching and soft switching; then in the soft switching, conducting analysis through a Stackelberg game to decide whether a vehicle is switched or not; finally, after a first application of the vehicle for switching fails, conducting a repeated application for switching through a BEB, and completing the switching by applying a game method again. According the method, the switching situation of the vehicle in the overlapping region of the RSU under the real environment can be simulated, the vehicle can select the right time slice to conduct the switching, the probability of congestion of the switching is reduced, the delivery rate of the network is improved, the vehicle can obtain better handling capacity, the whole performance of a VANET subnet is improved, and the user experience degree is improved.

Description

Changing method based on IEEE80211p in VANET

Technical field

The invention belongs to the mobile communication technology field, relate to the method for utilizing Staenberg game and binary exponential backoff algorithm to be switched the overlapping covered vehicle of roadside unit (Road Side Units, RSU); At the networking of the car based on the IEEE802.11p agreement (Vehicular Ad-hoc Network, VANET) in, provided concrete mobile communication switching method, the factors such as the signal strength signal intensity that vehicle can receive according to current vehicle fleet size, Vehicle Speed, the vehicle that need to switch and packet urgency, select suitable timeslice to be switched;

Background technology

In the VANET based on the IEEE802.11p agreement, a complete handoff procedure is divided into two parts: the switching of MAC layer and network layer switching; In MAC layer switching, mobile node is connected with new access node in physical layer, and is wirelessly connected between mobile node and new access point and sets up; For complete MAC layer switching, the wireless technology based on different, different handoff protocols may be employed; In the network layer switching, mobile node upgrades the routing table of oneself, and new routed path is created to maintain the communication of existence;

In the VANET of present stage based on the IEEE802.11p agreement, mainly there is the problem of following aspect in the research of changing method, vehicle is switched to the process of another RSU from a RSU, be all to improve the processes such as scanning, authentication to guarantee seamless switching, these all are based on the agreement thoughts such as IEEE802.11a/b/g, but IEEE802.11p has cancelled the authentication and associated process of the networks such as Wi-Fi, IEEE1609.3 regulation WSA (announcement of WAVE protocol service) can inform channel and the information on services of vehicle about RSU in advance, by reduce the switching congestion probability in processes such as scanning, authentications, guarantees that the method for seamless switching is not suitable for the VANET based on IEEE802.11p, for example: vehicle is divided into different set, select respectively a Mobile routing vehicle and an assistance vehicle in each set, these two can not be same vehicle, assisting vehicle is that the Mobile routing vehicle scans and find new RSU, by the RSU information of assisting vehicle collection buffer memory to close on, then whether the information in Mobile routing analysis assistance vehicle determines to be switched and (in VANET, based on NEMO, reduces switching delay, Azzedine Boukerche, Zhenxia Zhang, XinFei.Reducing Handoff Latency for NEMO-based Vehicular Ad Hoc Networks.Proc.of IEEE Global Communications Conference (Globecom) .Houston, TX, USA, 2011.1-5.), MIPv6 has ignored throughput, especially for multimedia application, can cause switching delay and the packet loss problem grown, fast moving IPv6 (FMIPv6) mechanism solves these problems of MIPv6 as possible, and it solves by handoff predictions, but the characteristic of the high-speed mobile of vehicle and break-in suddenly makes to predict uncertain, the look-ahead mechanism of FMIPv6 differs and improves surely handover mechanism (the robust switching based on unpredictable vehicle behavioural analysis in VANET, Hayoung Oh, Chong-kwon Kim.A Robust Handover under Analysis of Unexpected Vehicle Behaviors in Vehicular Ad-hoc Network.Proc.of Vehicular Technology Conference (VTC), Taipei, Taiwan, 2010.1-7.), utilize mobile IP v 6 (MIPv6) to combine to realize smoothness (a kind of seamless switching mechanism based on quality of video flowing in the VANET scene of city of video with forecasting mechanism, Mahdi Asefi, Sandra C ' espedes, Xuemin (Sherman) Shen, Jon W.Mark.A Seamless Quality-Driven Multi-Hop Data Delivery Scheme for Video Streaming in Urban VANET Scenarios.Proc.of International Conference on Communications (ICC), Kyoto, 2011.1-5.), a kind of cross-layer handover mechanism, utilize physical layer information and the information sharing of MAC layer to optimize handoff procedure (the quick handover mechanism of cross-layer in VANET, Kuan-Lin Chiu, Ren-Hung Hwang, Yuh-Shyan Chen.A Cross Layer Fast Handover Scheme in VANET.Proc.of IEEE International Conference on Communications (ICC), Dresden, 2009.1-5.), at RSU _mand RSU _nthe superimposed coverage area center relay station RS (Relay Station) is set, the coverage of sailing RS into when vehicle, and not yet roll RSU away from _mcoverage the time, RS receives RSU _mthe information on services provided to vehicle, continue as vehicle service, when vehicle sails RSU into _nduring with the coverage of RS, RS and RSU _ncommunication, pass through RSU _nfor vehicle provides service, thereby improve vehicle successful switch probability (the robustness handover mechanism that on highway, location and relaying are assisted, Linghui Lu, Xuming Fang, Meng Cheng, Chongzhe Yang, WantuanLuo, Cheng Di.Positioning and Relay Assisted Robust Handover Scheme for High Speed Railway.Proc.of Vehicular Technology Conference (VTC), Budapest, 2011.1-5.),

Summary of the invention

The technical problem to be solved in the present invention is to provide the method for switching in the scene that under a kind of Reality simulation environment, vehicle is denser at RSU, as Fig. 1, thereby reduce the congestion probability of switching, improve the network delivery rate, make vehicle obtain better throughput, improve the overall performance of VANET subnet, improve user experience;

Technical scheme of the present invention is as follows:

The factors such as signal strength signal intensity (RSSI), the load of RSU residual flow and packet urgency that receive by analyzing current vehicle fleet size, Vehicle Speed, the vehicle that need to switch, provided changing method, determined which timeslice which highway section switching vehicle should or advance in; When analyzing these factors, be divided into several levels and considered; At first, only consider that the signal strength signal intensity (RSSI) that vehicle receives determines whether being switched, and has been divided into direct-cut operation and soft handover; Then, in soft handover, by the Staenberg game, analyzed, determined whether vehicle switches; Finally, after vehicle first application handoff failure, carry out the application that repeats of sheet switching time by binary exponential backoff algorithm (BEB), then use game method to complete switching;

The changing method that the present invention proposes comprises three major parts:

Sheet switching time based on signal strength signal intensity is selected;

Sheet switching time based on the Staenberg game is selected;

Sheet switching time based on binary exponential backoff algorithm is selected;

Concrete steps are as follows:

(1) sheet switching time based on signal strength signal intensity is selected

In two adjacent RSU1 and the overlapping covered A of RSU2 or B, vehicle V _ithe most important condition of switching is vehicle V _ithe signal strength signal intensity (RSSI) that receives RSU1 is less than vehicle V _ireceive the signal strength signal intensity (RSSI) of RSU2; Suppose RSU1 and vehicle V _ithe signal strength signal intensity of communication is Q _{i, 1}, RSU2 and vehicle V _ithe signal strength signal intensity of communication is Q _{i, 2}, symbol W _i=Q _{i, 2}/ Q _{i, 1}, the analysis of shift process is as follows:

(2) sheet switching time based on the Staenberg game is selected

The resource that can provide due to RSU in VANET is limited, and the behavior of vehicle is free selfish behavior, and vehicle is all to use Internet resources from the number one competition; This meets the general hypothesis of non-cooperative game, so vehicle belongs to the non-cooperative game problem to the use of network shared resource;

Definition betting model F, F=<I, S, U >, I means all participants, and S means each participant's policy space, and U means each participant's utility function set;

The participant gathers I: the participant of game is the vehicle that in VANET, on same timeslice, application is switched, and the number of establishing the participant is n, the participant i ∈ I of game, and I={1,2 ..., i ... n};

Participant's policy space S: each participant selects certain strategy, S={S ₁, S ₂... S _i..., S _n; S _ibe the strategy that vehicle i selects, be made as binary number, i.e. S _i=0 or S _i=1, S _i=0 expression vehicle is selected not switch, S _i=1 means vehicle selection switching;

Participant's utility function U _i: as shown in formula (1),

U _i=A _i×B _i/C _i (1)

B wherein _ifor vehicle V _irevenue function, C _ifor vehicle V _icost function, A _imean vehicle V _iaction; In game, each action of participant can be for oneself bringing certain effectiveness, and this effectiveness is described by participant's utility function; Because the strategy of participant in game and action are all complementary, so each participant's effectiveness is relevant with other participant's strategy; Only have those to participate in the vehicle of task switching just need to pay cost and therefrom obtain income, do not participate in the vehicle of task switching for those, they need not pay any cost, certainly also can not get any income, therefore its value of utility is zero;

Vehicle is applied for switching on a timeslice, and sequencing is arranged in time, i.e. the not in the same time application switching of vehicle on sheet at the same time; Therefore, at first the strategy of the vehicle of application switching may be noticed by other vehicles, and this may have influence on the policy selection of other vehicles; In the game process, vehicle is all followed the strategy that certain order is selected them; Consider that the vehicle switching is the dynamic game process, we utilize the Staenberg game to solve the vehicle switching; It has the game process in two stages, and first stage is the leaders stage, supposes vehicle V _ifor the leader, it first makes the policy selection of oneself; Second stage is the followers stage, the dominant strategy of the policy selection oneself that vehicle is selected according to the leader; For the scene that n car arranged, each car is all selected the strategy of oneself in sequence; Vehicle V _iutility function be U _i, best selection strategy is, in the situation that other participants are constant, each participant maximizes the utility function U of oneself _i; The best set of strategies of all participants is to keep stablizing constant, and each participant has no reason to select other strategies, becomes Nash Equilibrium; Our ideal is the utility function U that tries to achieve each car _imaximum, i.e. Nash Equilibrium Solution;

Further decompose vehicle V for each variable in formula (1) _ithe action function, as formula (2):

Revenue function B _iwith cost function C _ias formula (3) and (4):

B _i=α×W _i×E _i×t×c _i (3)

C _i=β×P _i+H _cost (4)

Wherein, $c={w\log }_2(1+(S/N)/{\left(d_{{i,\mathrm{RSU}}_1}\right)}^{\mathrm{\&gamma;}}),$ C _i=c/min{TL, TL+n ₀-TLR}, for vehicle V _iwith RSU ₁distance, γ is the path fading index, c _ifor vehicle V _icommunication speed, n ₀for selecting the vehicle fleet size of switching, t=D/v, v is that car speed and D are that vehicle is at RSU ₁in the distance of travelling, t is the call duration time of vehicle in the RSU coverage; P _irSU ₁congestion probability, P _i=max{0, (n-TLR)/TLR}, H _costbe vehicle switching time, be definite value switching time here, and n is the vehicle fleet size of application switching;

By above analysis, formula (1) is evolved into formula (5):

$U_i=\frac{A_i\&times;\mathrm{\&alpha;}\&times;W_i\&times;E_i\&times;D\&times;\mathrm{\&omega;}{\log }_2(1+\frac{S}{N\&times;{\left(d_{i,\mathrm{RS}{U}_1}\right)}^{\mathrm{\&gamma;}}})}{\min (\mathrm{TL}+n_0-\mathrm{TLR})\&times;(\mathrm{\&beta;}\&times;P_i+H_{\cos t})\&times;v}---\left(5\right)$

Formula (5) has provided the expression formula of utility function, and following work is the maximum max U that solves utility function _i, make each vehicle can obtain maximum utility, try to achieve Nash Equilibrium Solution;

Utilize subgame Nash equilibrium (SPNE) to analyze the Staenberg game, if the participant can not increase his income by other strategies of one-side deflection in any stage, this subgame Nash equilibrium is a dominant strategy; Find out the SPNE of Staenberg game with backward induction; It progressively rises from the last stage of game, finally studies the first stage; The rationality vehicle of first carrying out in the Staenberg game, will inevitably consider rear behavior vehicle selection strategy how about in the stage in the back when the stage is selected behavior in front, only at the last stage of game, select, no longer include the vehicle that follow-up phase pins down, could directly make clearly and selecting; And, after the selection of last stages vehicle is determined, previous stage, the behavior of vehicle was also just easily determined; As shown in Figure 2, V wherein _imean to apply for the vehicle of switching, 0 expression vehicle is selected not switch, and 1 means vehicle selection switching; Vehicle V _ngame, at vehicle V _nselect under the dominant strategy condition, the vehicle of switch step is before selected a dominant strategy; If V ₁start to have selected not switch vehicle V ₂just according to V ₁result select oneself optimal policy; Equally, if V ₁start to have selected switching, vehicle V ₂can be according to V ₁result select oneself optimal policy; Then, this game theory analysis forwards a stage to, analyzes V ₁strategy; If V ₁selected not switch vehicle V ₂select dominant strategy, V ₁obtain an income; If vehicle V ₁selected switching, vehicle V ₂select dominant strategy, V ₁obtain an income; Compare these two income sizes, vehicle V ₁strategy in the time of will selecting a larger income, so just formed vehicle V ₁and V ₂dominant strategy, i.e. the SPNE of this game; By reverse conclusion, solve the maximum utility value max U of each vehicle _i;

(3) sheet switching time based on binary exponential backoff algorithm is selected

In the present invention, in order better to reduce the switching congestion probability, the time that adopts binary exponential backoff algorithm (BEB) thought in CSMA/CD to disperse the overlapping covered middle vehicle application switching of RSU; The time slice interval of vehicle application switching is divided into to time T, once, after vehicle application handoff failure, vehicle, for reducing the probability of again applying for handoff failure, needs to wait for a random time, and then the application switching; Adopt the process of binary exponential backoff algorithm as follows:

1., after the first application handoff failure occurring, vehicle waits for that 0 or 1 timeslice starts the application switching again;

2. after occurring to apply for handoff failure for the second time, vehicle selects to wait for 0,1,2 or 3 timeslice numbers randomly, then starts the application switching;

3. after applying for handoff failure the i time, 0 to 2 _iselect randomly the timeslice number of a wait between-1, then start the application switching;

4. until vehicle V _ithe signal strength signal intensity Q communicated by letter with former RSU _i=0, vehicle is carried out direct-cut operation;

In the overlapping covered A and B of two adjacent RSU1 and RSU2, the whole handoff procedure of consideration as shown in Figure 3;

Effect of the present invention and benefit be can the Reality simulation environment under vehicle in the situation of the overlapping region of RSU switching, make vehicle select suitable timeslice to be switched, reduce the congestion probability of switching, improve the network delivery rate, make vehicle obtain better throughput, improve the overall performance of VANET subnet, improve user experience;

The accompanying drawing explanation

Accompanying drawing 1 is the schematic diagram of handoff scenario;

Accompanying drawing 2 is Staenberg game theory reduced graphs

Accompanying drawing 3 is schematic diagrames of handoff procedure;

Accompanying drawing 4 is schematic diagrames of embodiment scene;

Accompanying drawing 5 is schematic diagrames that vehicle obtains average throughput;

Accompanying drawing 6 is schematic diagrames of network delivery rate;

Accompanying drawing 7 (a) is based on the schematic diagram of the switching congestion probability of Staenberg game;

Accompanying drawing 7 (b) is based on the schematic diagram of the switching congestion probability of binary exponential backoff algorithm;

Embodiment

Describe embodiments of the invention in detail below in conjunction with technical scheme and accompanying drawing;

The improvement situation of the average throughput of the switching congestion probability of the vehicle that RSU is overlapping covered, network delivery rate and vehicle is described by embodiment under the method proposed in the present invention; As shown in Figure 4, between RSU1 and RSU2, at a distance of 600m, overlapping covered is C and D part, because regional C and D are symmetrical, and present analyzed area C; In the C zone, road maximum length GH is 200m, considers that the Ordinary Rd width is 10m, with respect to GH length; Road width is less, so camber line EGF regards straight line as; In the scene of city, car speed is generally lower, supposes that car speed is 10m/s, and the safe distance between vehicle is 15m-20m; Thus, 40 vehicles are at most approximately arranged in regional C and D; In embodiment, the overlapping covered vehicle fleet size of RSU1 and RSU2 is set to 5-50; Parameter value is as table 1;

Table 1

(1) throughput

In Fig. 5, find out that the vehicle average throughput overlapping covered at RSU is relevant with vehicle fleet size; By the relatively variation of the method based on the present invention's proposition and the lower vehicle average throughput of the signal strength signal intensity based on RSU (RSSI), find out, when vehicle is increased to 25 from 5, the average throughput of vehicle descends very fast, continuation growth along with vehicle fleet size, the average throughput pace of change that vehicle obtains is slack-off, this is from 5 processes that are increased to 25 because of the overlapping covered vehicle of RSU, be vehicle switching gradually from without congestion state to the process that vehicle switching congestion state occurs, this also meets the impact of congestion probability on the vehicle throughput; With the RSSI method, compare, the method that the present invention proposes can make vehicle obtain larger throughput, obtains better QoS, has improved user's Experience Degree;

(2) network delivery rate

Fig. 6 has provided the relation between the overlapping covered vehicle fleet size of RSU and network delivery rate, along with the increase of vehicle, and the reduction of network delivery rate fluctuation; When vehicle is increased to 25 from 5, based on the RSSI method, with the method proposed based on the present invention, to compare, network delivery rate difference is little; When vehicle, during more than 25, the network delivery rate based on put forward the methods of the present invention is significantly better than the network delivery rate based on the RSSI method, i.e. the method that the present invention proposes can effectively be improved VANET subnet performance;

(3) congestion probability

The method that the present invention proposes, reduce the congestion probability that vehicle switches from two aspects, the congestion probability when the game process has been considered the vehicle switching; Using binary exponential backoff algorithm, is also in order to reduce the congestion probability of vehicle switching; From Fig. 7 (a), find out, when the overlapping covered vehicle fleet size of RSU is less, the switching congestion probability is zero; When the overlapping covered vehicle of RSU reaches some, along with the increase of vehicle, the switching congestion probability increases gradually; Congestion probability based on game is slightly lower than the congestion probability based on RSSI, this is because in betting model, utility function is except the signal strength signal intensity (RSSI) of considering to communicate by letter between vehicle and RSU, also consider at the same time and apply for the vehicle fleet size switched on sheet, when on sheet at the same time, the vehicle fleet size of application switching is more, the part vehicle is selected not switch because obtain less value of utility, thereby has reduced the congestion probability of switching; Switching congestion probability when Fig. 7 (b) has compared use and do not used binary exponential backoff algorithm; When vehicle is less, the switching congestion probability is zero; When vehicle reaches some, along with the increase of the overlapping covered vehicle fleet size of RSU, the switching congestion probability increases gradually; When the switching vehicle fleet size is greater than 20, use binary exponential backoff algorithm can significantly reduce congestion probability; , just consider that vehicle is all to apply for switching after failure for the first time here, consider radix-2 algorithm situation worst, vehicle can only wait for that 0 or 1 timeslice is switched; Under normal circumstances, vehicle application handoff failure number of times more than once, according to binary exponential backoff algorithm, vehicle can better be distributed on how different timeslices applies for switching, so use binary exponential backoff algorithm can obtain lower congestion probability.

Claims (1)

1.VANET in changing method based on IEEE802.11p, it is characterized in that, this changing method comprises:

Sheet switching time based on signal strength signal intensity is selected;

Sheet switching time based on the Staenberg game is selected;

Sheet switching time based on binary exponential backoff algorithm is selected;

Specific as follows:

(1) sheet switching time based on signal strength signal intensity is selected

In two adjacent RSU1 and the overlapping covered A of RSU2 or B, vehicle V _ithe most important condition of switching is vehicle V _ithe signal strength signal intensity (RSSI) that receives RSU1 is less than vehicle V _ireceive the signal strength signal intensity (RSSI) of RSU2; Suppose RSU1 and vehicle V _ithe signal strength signal intensity of communication is Q _{i, 1}, RSU2 and vehicle V _ithe signal strength signal intensity of communication is Q _{i, 2}, symbol W _i=Q _{i, 2}/ Q _{i, 1}, the analysis of shift process is as follows:

(2) sheet switching time based on the Staenberg game is selected

The resource that can provide due to RSU in VANET is limited, and the behavior of vehicle is free selfish behavior, and vehicle is all to use Internet resources from the number one competition; This meets the general hypothesis of non-cooperative game, so vehicle belongs to the non-cooperative game problem to the use of network shared resource;

Definition betting model F, F=<I, S, U >, I means all participants, and S means each participant's policy space, and U means each participant's utility function set;

The participant gathers I: the participant of game is the vehicle that in VANET, on same timeslice, application is switched, and the number of establishing the participant is n, the participant i ∈ I of game, and I={1,2 ..., i ... n};

Participant's policy space S: each participant selects certain strategy, S={S ₁, S ₂... S _i..., S _n; S _ibe the strategy that vehicle i selects, be made as binary number, i.e. S _i=0 or S _i=1, S _i=0 expression vehicle is selected not switch, S _i=1 means vehicle selection switching;

Participant's utility function U _i: as shown in formula (1),

U _i=A _i×B _i/C _i (1)

B wherein _ifor vehicle V _irevenue function, C _ifor vehicle V _icost function, A _imean vehicle V _iaction;

In game, each action of participant can be for oneself bringing certain effectiveness, and this effectiveness is described by participant's utility function; Because the strategy of participant in game and action are all complementary, so each participant's effectiveness is relevant with other participant's strategy; Only have those to participate in the vehicle of task switching just need to pay cost and therefrom obtain income, do not participate in the vehicle of task switching for those, they need not pay any cost, certainly also can not get any income, therefore its value of utility is zero;

Vehicle is applied for switching on a timeslice, and sequencing is arranged in time, i.e. the not in the same time application switching of vehicle on sheet at the same time; Therefore, at first the strategy of the vehicle of application switching may be noticed by other vehicles, and this may have influence on the policy selection of other vehicles; In the game process, vehicle is all followed the strategy that certain order is selected them; Consider that the vehicle switching is the dynamic game process, we utilize the Staenberg game to solve the vehicle switching; It has the game process in two stages, and first stage is the leaders stage, supposes vehicle V _ifor the leader, it first makes the policy selection of oneself; Second stage is the followers stage, the dominant strategy of the policy selection oneself that vehicle is selected according to the leader; For the scene that n car arranged, each car is all selected the strategy of oneself in sequence; Vehicle V _iutility function be U _i, best selection strategy is, in the situation that other participants are constant, each participant maximizes the utility function U of oneself _i; The best set of strategies of all participants is to keep stablizing constant, and each participant has no reason to select other strategies, becomes Nash Equilibrium; Our ideal is the utility function U that tries to achieve each car _imaximum, i.e. Nash Equilibrium Solution;

Further decompose vehicle V for each variable in formula (1) _ithe action function, as formula (2):

Revenue function B _iwith cost function C _ias formula (3) and (4):

B _i=α×W _i×E _i×t×c _i (3)

C _i=β×P _i+H _cost (4)

Wherein, $c={w\log }_2(1+(S/N)/{\left(d_{{i,\mathrm{RSU}}_1}\right)}^{\mathrm{\&gamma;}}),$ C _i=c/min{TL, TL+n ₀-TLR}, for vehicle V _iwith RSU ₁distance, γ is the path fading index, c _ifor vehicle V _icommunication speed, n ₀for selecting the vehicle fleet size of switching, t=D/v, v is that car speed and D are that vehicle is at RSU ₁in the distance of travelling, t is the call duration time of vehicle in the RSU coverage; P _irSU ₁congestion probability, P _i=max{0, (n-TLR)/TLR}, H _costbe vehicle switching time, be definite value switching time here, and n is the vehicle fleet size of application switching;

By above analysis, formula (1) is evolved into formula (5):

$U_i=\frac{A_i\&times;\mathrm{\&alpha;}\&times;W_i\&times;E_i\&times;D\&times;\mathrm{\&omega;}{\log }_2(1+\frac{S}{N\&times;{\left(d_{i,\mathrm{RS}{U}_1}\right)}^{\mathrm{\&gamma;}}})}{\min (\mathrm{TL}+n_0-\mathrm{TLR})\&times;(\mathrm{\&beta;}\&times;P_i+H_{\cos t})\&times;v}---\left(5\right)$

Formula (5) has provided the expression formula of utility function, and following work is the maximum max U that solves utility function _i, make each vehicle can obtain maximum utility, try to achieve Nash Equilibrium Solution;

Utilize subgame Nash equilibrium (SPNE) to analyze the Staenberg game, if the participant can not increase his income by other strategies of one-side deflection in any stage, this subgame Nash equilibrium is a dominant strategy; Find out the SPNE of Staenberg game with backward induction; It progressively rises from the last stage of game, finally studies the first stage; The rationality vehicle of first carrying out in the Staenberg game, will inevitably consider rear behavior vehicle selection strategy how about in the stage in the back when the stage is selected behavior in front, only at the last stage of game, select, no longer include the vehicle that follow-up phase pins down, could directly make clearly and selecting; And, after the selection of last stages vehicle is determined, previous stage, the behavior of vehicle was also just easily determined; By reverse conclusion, solve the maximum utility value max U of each vehicle _i;

(3) sheet switching time based on binary exponential backoff algorithm is selected

In the present invention, in order better to reduce the switching congestion probability, the time that adopts binary exponential backoff algorithm (BEB) thought in CSMA/CD to disperse the overlapping covered middle vehicle application switching of RSU; The time slice interval of vehicle application switching is divided into to time T, once, after vehicle application handoff failure, vehicle, for reducing the probability of again applying for handoff failure, needs to wait for a random time, and then the application switching; Adopt the process of binary exponential backoff algorithm as follows:

1., after the first application handoff failure occurring, vehicle waits for that 0 or 1 timeslice starts the application switching again;

2. after occurring to apply for handoff failure for the second time, vehicle selects to wait for 0,1,2 or 3 timeslice numbers randomly, then starts the application switching;

3. after applying for handoff failure the i time, 0 to 2 _iselect randomly the timeslice number of a wait between-1, then start the application switching;

4. until vehicle V _ithe signal strength signal intensity Q communicated by letter with former RSU _i=0, vehicle is carried out direct-cut operation.

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