CN110933648A - Vehicle-mounted ad hoc network clustering method based on link reliability - Google Patents

Vehicle-mounted ad hoc network clustering method based on link reliability Download PDF

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CN110933648A
CN110933648A CN201911303097.2A CN201911303097A CN110933648A CN 110933648 A CN110933648 A CN 110933648A CN 201911303097 A CN201911303097 A CN 201911303097A CN 110933648 A CN110933648 A CN 110933648A
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虞慧群
范贵生
吉祥
杨星光
刘冬梅
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East China University of Science and Technology
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    • 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]
    • H04W4/48—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for in-vehicle communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

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Abstract

The invention relates to a vehicle-mounted ad hoc network clustering method based on link reliability, which comprises the following steps: step S1: establishing a vehicle motion model according to vehicle nodes in a vehicle-mounted ad hoc network, and calculating the link survival time between the vehicle nodes; step S2: evaluating the reliability of the link between the vehicle nodes according to the link survival time of the step S1; step S3: and finishing cluster head selection, cluster formation and cluster maintenance of the vehicle-mounted ad hoc network according to the link reliability by adopting a vehicle-mounted ad hoc network clustering algorithm. Compared with the prior art, the method has the advantages of improving the clustering efficiency of the vehicle-mounted self-organization and the stability of the clusters and the like.

Description

Vehicle-mounted ad hoc network clustering method based on link reliability
Technical Field
The invention relates to the field of vehicle ad hoc networks, in particular to a vehicle ad hoc network clustering method based on link reliability.
Background
There are three networking modes for Vehicular Ad Hoc networks (VANET), i.e., centralized, distributed, and hybrid. The hybrid network architecture has been widely researched due to the advantages of network self-organization and flexible deployment in the distributed network architecture, and the advantages of wide communication range and internet access in the centralized network architecture. However, the hybrid network architecture needs to deploy more infrastructure such as roadside units to ensure that the network has enough access points to access and acquire the internet and the upper-layer rich applications. In order to fully utilize the advantages of the hybrid architecture under the condition of deploying limited infrastructure, a clustering idea is introduced into the hybrid architecture, as shown in fig. 1, by clustering vehicle nodes in a VANET, a cluster head can directly communicate with fixed infrastructure, intra-cluster communication is managed by the cluster head, and thus communication overhead between the vehicle and the infrastructure can be effectively reduced. The clustering algorithm has good expandability, and can improve the flexibility and the expandability of the route design. Therefore, how to design an effective clustering method is crucial to the VANET of the hybrid architecture.
At present, more effective clustering methods for the VANET exist, but due to the characteristics of high mobility of a vehicle-mounted network and frequent change of network topology, the stability of a cluster in the network cannot be guaranteed by the traditional clustering algorithms. In addition, the existing method mainly selects the cluster head node according to the node mobility characteristics, and the influence of the link reliability factor of the node on the cluster head selection is not considered, so that the stability of the cluster in the network cannot be ensured.
Disclosure of Invention
The invention aims to provide a vehicle ad hoc network clustering method based on link reliability to overcome the defect of poor stability of clustering in the vehicle ad hoc network in the prior art.
The purpose of the invention can be realized by the following technical scheme:
a vehicle-mounted ad hoc network clustering method based on link reliability comprises the following steps:
step S1: establishing a vehicle motion model according to vehicle nodes in a vehicle-mounted ad hoc network, and calculating the link survival time between the vehicle nodes;
step S2: evaluating the reliability of the link between the vehicle nodes according to the link survival time of the step S1;
step S3: and finishing cluster head selection, cluster formation and cluster maintenance of the vehicle-mounted ad hoc network according to the link reliability by adopting a vehicle-mounted ad hoc network clustering algorithm, wherein the cluster formation refers to the establishment of a cluster in the vehicle-mounted ad hoc network, and the cluster maintenance refers to the maintenance and the update of the cluster.
The vehicle space distribution of the vehicle ad hoc network is defined to obey a lognormal distribution, and specifically comprises the following steps:
Xi∈logN(μi，δi)
wherein, muiAnd deltaiIs a normally distributed parameter, Xi＝{Xi(τ), τ is 0,1, 2. } is the distance between vehicle node i and vehicle node i +1, Xi(τ) represents the inter-vehicle distance between the vehicle node i and the vehicle node i +1 at the time τ.
The link lifetime is the time for which the link of two vehicle nodes lasts from the beginning of the link to the disconnection.
The link reliability is the possibility that two vehicle nodes can continuously and directly communicate within a period of time, and is expressed by conditional probability, specifically:
Figure BDA0002322350210000021
wherein, TpIs a time interval, rt(lij) For link reliability, Erf is a Gaussian error function, Δ vijRelative velocity, μ Δ v, of two vehicle nodesijAnd
Figure BDA0002322350210000022
is a relative velocity DeltavijT is the current time, and R is the communication radius of the vehicle node.
And when the Euclidean distance between the two vehicle nodes is smaller than the communication radius, the two vehicle nodes become neighbor nodes.
The vehicle node acquires and updates the information of the neighbor nodes through a beacon mechanism, and stores the information of the neighbor nodes by constructing a potential neighbor node set.
The candidate object selected by the cluster head and formed by the cluster is a vehicle node filtered by a preprocessing mechanism of a neighbor sampling method, and the neighbor sampling method is based on the link survival time.
The cluster maintenance comprises cluster head re-election, cluster fusion and intra-cluster updating.
The cluster head re-election calculates the probability evaluation whether the new vehicle node is accepted as the cluster head node or not, wherein the current state is replaced by the new state added to the new vehicle node, through Metropolis receiving criteria in an annealing algorithm.
The states of the vehicle nodes in the vehicle-mounted ad hoc network clustering algorithm comprise an initial state, a cluster head node state, a cluster member node state or a candidate cluster member state.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention fully considers the high-speed mobility of the vehicle nodes in the vehicle-mounted ad hoc network, takes the link survival time as the evaluation index of the link reliability, and can effectively reduce the probability of link fracture.
2. According to the invention, through a preprocessing mechanism of a neighbor sampling method based on link survival time, vehicle nodes with poor stability are filtered in advance, redundant calculation is reduced, and clustering efficiency and cluster stability are improved.
3. In the cluster maintenance process, the Metropolis receiving criterion in the annealing algorithm is used for evaluating whether a new vehicle node is accepted as a cluster head node, so that the change of a cluster structure caused by micro stirring is reduced, and the stability of the cluster is improved.
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Fig. 1 is a schematic structural diagram of a vehicle networking architecture based on VANET clustering;
FIG. 2 is a schematic flow chart of the present invention;
FIG. 3 is a schematic representation of a vehicle motion model of the present invention;
FIG. 4(a) is a schematic diagram of two vehicle nodes traveling in the same direction and having a forward vehicle speed greater than a backward vehicle speed in a link lifetime calculation scenario according to the present invention;
FIG. 4(b) is a schematic diagram of two vehicle nodes traveling in the same direction and having a front vehicle speed less than a rear vehicle speed in a link lifetime calculation scenario according to the present invention;
FIG. 4(c) is a schematic diagram of two vehicle nodes approaching in reverse directions in a link lifetime calculation scenario according to the present invention;
FIG. 4(d) is a schematic diagram illustrating reverse direction of two vehicle nodes away in a link lifetime calculation scenario according to the present invention;
fig. 5 is a schematic diagram of the beacon mechanism of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
As shown in fig. 2, a method for clustering a vehicle ad hoc network based on link reliability includes the following steps:
step S1: establishing a vehicle motion model according to vehicle nodes in a vehicle-mounted ad hoc network, and calculating the link survival time between the vehicle nodes;
step S2: evaluating the reliability of the link between the vehicle nodes according to the link survival time of the step S1;
step S3: and finishing cluster head selection, cluster formation and cluster maintenance of the vehicle-mounted ad hoc network according to the link reliability by adopting a vehicle-mounted ad hoc network clustering LRCA algorithm.
For the vehicle operation model, only a general highway scene is considered, influence of extremely special scenes such as a road slope and a tunnel is ignored, since a vehicle communication range is much larger than a road width, and influence of the road width is also ignored, the general highway scene is as shown in fig. 3, and vehicle spatial distribution on a straight road at a certain distance is defined to obey a lognormal distribution, specifically:
Xi∈logN(μi，δi)
wherein, muiAnd deltaiIs a normally distributed parameter, Xi＝{Xi(τ), τ is 0,1, 2. } is the distance between vehicle node i and vehicle node i +1, Xi(τ) represents the inter-vehicle distance between the vehicle node i and the vehicle node i +1 at the time τ.
As shown in fig. 3, with V0Is a reference node, then V0Distance to any node is X ═ X1+X2+…+XτWhere X also follows a normal distribution.
The link survival time is the time of the link of two vehicle nodes from the link start to the disconnection, each vehicle has the same communication radius R, and the vehicle nodes keep running at a constant speed,
as shown in FIG. 4(a), two vehicle nodes ViAnd VjRunning on the same road in the same direction at speeds viAnd vjA distance d between themijAnd d isij< R, vehicle node V located behindiIs greater than the vehicle node V in frontjVelocity of, i.e. vi＞vjWhen the rear vehicle node overtakes the front vehicle node and exceeds the front vehicle node by a distance greater than R, the link between the two vehicle nodes is disconnected, and the link survival time LLT is reachedijThe method specifically comprises the following steps:
Figure BDA0002322350210000041
as shown in FIG. 4(b), two vehicle nodes ViAnd VjRunning on the same road in the same direction at speeds viAnd vjA distance d between themijAnd d isij< R, vehicle node V located behindiIs less than the vehicle node V aheadjVelocity of, i.e. vi＜vjThe distance between two vehicle nodes will be enlarged continuously when the distance between two vehicle nodesWhen the distance exceeds R, the link between two vehicle nodes is disconnected, and the link survival time LLT is upijThe method specifically comprises the following steps:
Figure BDA0002322350210000042
if the speeds of the two vehicle nodes are the same, i.e. vi＝vjIf the two vehicle nodes keep running at a constant speed, the link between the two vehicle nodes is extremely stable;
as shown in FIG. 4(c), two vehicle nodes ViAnd VjRun on the same road in opposite directions at speeds viAnd vjA distance d between themijAnd d isij< R, when the relative distance of two vehicle nodes is from + dijWhen changing to-R, i.e. relative movement R + dijAfter the distance, the links of the two vehicle nodes are disconnected, and the link survival time LLT is up to the momentijThe method specifically comprises the following steps:
Figure BDA0002322350210000051
as shown in FIG. 4(d), two vehicle nodes ViAnd VjTravelling on the same road in opposite directions at speeds viAnd vjA distance d between themijAnd d isij< R, when two vehicle nodes move relatively R-dijAfter the distance, the links of the two vehicle nodes are disconnected, and the link survival time LLT is up to the momentijThe method specifically comprises the following steps:
Figure BDA0002322350210000052
the link reliability is the possibility that two vehicle nodes can continuously and directly communicate within a period of time, and is expressed by conditional probability, specifically:
Figure BDA0002322350210000053
wherein, TpIs a time interval, rt(lij) For link reliability, Erf is a Gaussian error function, Δ vijRelative velocity, μ Δ v, of two vehicle nodesijAnd
Figure BDA0002322350210000054
is a relative velocity DeltavijT is the current time, and R is the communication radius of the vehicle node.
The states of the vehicle nodes IN the clustering algorithm of the vehicle-mounted ad hoc network comprise an initial state IN, a cluster head node state CH, a cluster member node state CM or a candidate cluster member state CCM.
The method comprises the steps that the initial state of each vehicle node IN a vehicle-mounted ad hoc network is an initial state IN, the vehicle nodes acquire and update information of neighbor nodes through a beacon mechanism IN an initial state time interval IN _ TIMER, if one vehicle node sniffs that a cluster head node exists IN a hop range of the vehicle node IN the IN _ TIMER, a cluster application packet JOIN _ REQ is sent to the corresponding cluster head node to request to JOIN the existing cluster, the state of the vehicle node is changed into CCM, and meanwhile, a TIMER JOIN _ TIMER is set; otherwise, when the IN _ TIMER is finished and the vehicle node does not find a cluster head node IN the one-hop range, if the vehicle node meets the condition of becoming a cluster head, the vehicle node changes the state of the vehicle node into a CH node. When the vehicle node in the state of CCM receives a cluster admission feedback message CH _ RESP from the CH node before the JOIN _ TIMER time is over, the vehicle node changes the state of the vehicle node into a cluster member CM; otherwise, it reverts the state back to the IN state. When a vehicle node IN the CM state loses connection with the cluster head for a long time, the vehicle node is removed from the cluster, and the node state is reset to IN. Due to the dynamic change of the vehicle nodes, the situation that the overlap degree between clusters is high may occur, and whether the clusters need to be merged needs to be judged. For the vehicle node in the CH state, if the vehicle node receives the acknowledgement MERGE message MERGE _ ACK sent from other cluster head nodes, the vehicle node converts the state into the CM; if a cluster head re-election process occurs or the CH node becomes an isolated cluster head node within a period of time, namely, no member IN the cluster exists, the state is converted into the IN node.
When the Euclidean distance between two vehicle nodes is smaller than the communication radius, the two vehicle nodes become neighbor nodes, the vehicle nodes acquire and update the information of the neighbor nodes through a Beacon Beacon mechanism, the information of the neighbor nodes is stored by constructing a potential neighbor node set, and the set of the neighbor nodes is specifically as follows:
PNi＝{Vj|dij＜R}
wherein d isijRepresenting two vehicle nodes ViAnd VjThe distance between them.
The Beacon Beacon has a structure of six tuples, specifically
Beacon＝<VID，(x，y)，v，dir，S，CHID>
Wherein, VIDDenotes the number of the vehicle node, (x, y) denotes the position of the vehicle node, v denotes the current speed of the vehicle, dir denotes the direction of travel of the vehicle, S denotes a status identifier of the vehicle, CHIDA number indicating a cluster head vehicle of a cluster in which the vehicle is located. After receiving the Beacon Beacon message, the vehicle node records the related information of the neighbor vehicle through the neighbor table.
As shown in fig. 5, the vehicle node periodically broadcasts Beacon messages within the communication radius as shown in D1, and adds or updates the information of the neighboring vehicle nodes in the neighbor table according to the received Beacon messages as shown in D2, if the vehicle node does not receive the Beacon message updated by a neighboring node within a certain time interval (usually, two Beacon intervals), the neighboring node is considered to be no longer a neighboring node, and the information of the neighboring node is deleted from the neighbor table of the vehicle node.
The candidate object selected by the cluster head and formed by the cluster is a vehicle node filtered by a preprocessing mechanism of a neighbor sampling method, namely a stable neighbor vehicle set SN, and the neighbor sampling method is based on the link survival time.
The process of the neighbor sampling method specifically includes setting an initial state time interval IN _ TIMER, within which a vehicle node V is set to a TIMER durationiThrough Beacon messageAcquiring and updating the related information of the neighbor node, and calculating the related information of the neighbor node VjInter link lifetime LLTijWhen the link survival time LLT is estimatedijExceeding a set threshold deltasTime, neighbor node VjIs selected as the vehicle node ViStable neighbor nodes.
For a stable neighbor node of a vehicle node, in the process of cluster head selection, a cluster head capability parameter needs to be calculated, where the cluster head capability parameter LREL specifically is:
Figure BDA0002322350210000071
wherein, LRELiRepresenting a vehicle node ViT represents the current time, SNiRepresenting a vehicle node ViA stable set of neighbor nodes.
If a vehicle node has a larger LREL value, which means that the node has higher link reliability with surrounding direct neighbor nodes, the vehicle node having the larger LREL value is selected as a cluster head node, so that the cluster can be more stable, and the cluster maintenance time is longer.
The specific process of cluster head selection includes for a vehicle node V IN the IN stateiIn the TIMER CH _ TIMER time, firstly, the vehicle node V tries to join an existing cluster by monitoring a CH _ ACK packet in a one-hop range or a Beacon message from a cluster head node, and if the vehicle node sniffs that the cluster head node CH exists in the one-hop range, the vehicle node ViSending a cluster entering request packet JOIN _ REQ to a cluster head node CH, changing the state of the cluster entering request packet JOIN _ REQ into CCM and jumping to a clustering process stage. If CH _ TIMER time runs out and ViNo suitable cluster, V, has been foundiWhether the cluster head node can be formed into a cluster head node is evaluated, and the cluster head capability parameter LREL of the cluster head node is calculatediAnd mixing it with SNiCluster head capability parameter LREL of vehicle node in (1)jMaking a comparison if ViFinding the highest self cluster head capability parameter, ViDeclares itself to be a cluster head node CH and broadcasts BThe eacon message informs the corresponding neighbor nodes to start building the own cluster; otherwise ViThe above process is repeated.
The specific process of cluster formation includes for a vehicle node V IN the IN statejFirst, an attempt is made to connect to an already existing cluster. If VjAfter receiving a CH _ ACK packet of a neighborhood space or a Beacon message from a cluster head node, the node first sends a JOIN _ REQ message requesting to JOIN to the cluster head node, and converts the status into CCM, and then sets a TIMER JOIN _ TIMER to wait for a feedback message of the cluster head node. If V is within the JOIN _ TIMER timejA feedback message JOIN _ RESP is received from the cluster head indicating that it is allowed to JOIN the cluster, VjThe status of itself is changed to CM. Otherwise VjResetting the self state to IN and retrying the process;
vehicle node V for CH stateiWhen it receives the signal from the vehicle node VjWhen requesting the packet JOIN _ REQ, it first checks its own cluster member number, and ignores the vehicle node V if the number of managed CMs reaches the threshold upper limit MAX _ CMjIs requested. Otherwise, ViWill VjAdding information of CM _ LISTiIn a direction of VjAn acknowledgement message JOIN _ RESP is sent.
The cluster maintenance comprises cluster head re-election, cluster fusion and intra-cluster updating. Since the LRCA algorithm defines the maximum number of members in a cluster during clustering, there is no need to consider the cluster splitting case here.
The cluster head re-election calculates the probability evaluation whether the new vehicle node is accepted as the cluster head node or not, wherein the current state is replaced by the new state added to the new vehicle node, through Metropolis receiving criteria in an annealing algorithm. At time t0When clusters of vehicle nodes in the vehicle ad hoc network are formed, and for a cluster, the cluster head node is A, and the cluster head capability parameter is LRELA(t0) And in the cluster member node B, the cluster head capability parameter is LRELB(t0) Now LREL is apparentA(t0)＞LRELB(t0) As time goes on, at time t, the cluster head capability parameters of the two become LREL respectivelyA(t) and LRELB(t), then:
when LRELA(t)＞LRELB(t), namely when the cluster head capability parameter of the vehicle node A is still larger than that of the vehicle node B, the vehicle node A continues to act as a cluster head node, and the structure in the cluster is not changed;
when LRELA(t)＜LRELB(t), that is, when the cluster head capability parameter of the vehicle node a is smaller than that of the vehicle node B, the cluster head of the vehicle node a is challenged by the member B in the cluster, and the acceptance probability of the vehicle node B is specifically p ═ 1-exp (LREL)A(t)-LRELB(t)), and is associated with a random number δ ∈ (0, 1)]By comparison, if p > δ, the member node B will become the new cluster head node.
When a cluster head node a is subjected to a challenge from a member node B in a cluster, the probability of accepting the member node B as a new cluster head node is specifically:
Figure BDA0002322350210000081
where δ represents a random number within (0, 1), and p (t) represents the acceptance probability of the member node B, the formula is as follows:
p(t)＝1-exp(min{0，LRELA(t)-LRELB(t)})
where exp denotes an exponential function.
The process of cluster fusion specifically comprises that when cluster head nodes CH in two clustersiAnd CHjWhen the cluster becomes a neighbor node, the two clusters are overlapped, and the link survival time LLT between the two clusters is calculatedijIf LLT is presentijAnd if the threshold value is exceeded, triggering the fusion process of the cluster. In the fusion process, two cluster head nodes share the information of vehicle nodes in the cluster, and the cluster head capability parameters of the two cluster head nodes are compared, and the cluster head node CH with smaller valuejTo the cluster head node CH with larger capability valueiA MERGE request MERGE _ ACK is issued. When CH is presentiAfter receiving the MERGE _ ACK message, the fused potential cluster size is calculated:
Npm＝NUM_CM(CHi)+{NUM(Vk)|Vk∈CM_LISTj&&dik＜R}
wherein N ispmIndicating the potential cluster size, NUM _ CM (CH)i) Representing the number of member nodes, V, in the current clusterkIndicates in CHjMember node in the cluster, NUM (V)k) Indicates recording in CHiIn the cluster, CM _ LISTjRepresents CHjMember node list of dikRepresents CHiAnd VkThe distance between them.
If N is presentpmLess than the upper size limit MAX _ CM of the cluster, then merging is allowed, CHiTo CHjAnd sending a MERGE _ RESP data packet which contains the fused intra-cluster node information. CH (CH)jAfter receiving the MERGE _ RESP, the merged member node is informed to be directly added into the CHiIn a cluster, and disburse other nodes, then CHjAbandoning the cluster head state and converting the self state into CM, and adding into the fused cluster.
The intra-cluster updating process specifically includes that during each Beacon, each cluster head node CH dynamically monitors its connection with the intra-cluster member nodes CMs. When the CH receives a message from a member node CM in the cluster, it will update the relevant information for that member node in the CM _ LIST. If the CH does not receive Beacon messages from the member node CM in the cluster in two consecutive Beacon intervals, the connection between the member node CM and the CH is considered to be lost, namely the member node and related information are removed from the CM _ LIST by the CH node, which indicates that the node does not belong to the current cluster any more; similarly, when a member node CM IN a cluster finds that it has lost its connection with the cluster head node to which it belongs between two consecutive beacon intervals, it resets its own state to IN and retries to join a new cluster.
In addition, it should be noted that the specific embodiments described in the present specification may have different names, and the above descriptions in the present specification are only illustrations of the structures of the present invention. Minor or simple variations in the structure, features and principles of the present invention are included within the scope of the present invention. Various modifications or additions may be made to the described embodiments or methods may be similarly employed by those skilled in the art without departing from the scope of the invention as defined in the appending claims.

Claims (10)

1. A vehicle-mounted ad hoc network clustering method based on link reliability is characterized by comprising the following steps:
step S1: establishing a vehicle motion model according to vehicle nodes in a vehicle-mounted ad hoc network, and calculating the link survival time between the vehicle nodes;
step S2: evaluating the reliability of the link between the vehicle nodes according to the link survival time of the step S1;
step S3: and finishing cluster head selection, cluster formation and cluster maintenance of the vehicle-mounted ad hoc network according to the link reliability by adopting a vehicle-mounted ad hoc network clustering algorithm.
2. The method for clustering the vehicle ad hoc network based on the link reliability as claimed in claim 1, wherein the vehicle spatial distribution of the vehicle ad hoc network is defined to obey a lognormal distribution, specifically:
Xi∈logN(μi,δi)
wherein, muiAnd deltaiIs a normally distributed parameter, Xi＝{Xi(τ), τ ═ 0,1,2 … } is the distance between vehicle node i and vehicle node i +1, Xi(τ) represents the inter-vehicle distance between the vehicle node i and the vehicle node i +1 at the time τ.
3. The vehicle ad hoc network clustering method based on link reliability as claimed in claim 1, wherein the link lifetime is a time duration from a link start to a link disconnection of two vehicle nodes.
4. The method according to claim 1, wherein the link reliability is a possibility that two vehicle nodes can continuously and directly communicate within a time interval, and is expressed by a conditional probability, specifically:
Figure FDA0002322350200000011
wherein, TpIs a time interval, rt(lij) For link reliability, Erf is a Gaussian error function, Δ vijThe relative velocities of two vehicle nodes are the,
Figure FDA0002322350200000012
and
Figure FDA0002322350200000013
is a relative velocity DeltavijT is the current time, and R is the communication radius of the vehicle node.
5. The method according to claim 4, wherein when the Euclidean distance between two vehicle nodes is smaller than the communication radius, the two vehicle nodes become neighbor nodes.
6. The vehicle ad hoc network clustering method based on link reliability according to claim 5, wherein the vehicle node acquires and updates information of neighbor nodes through a beacon mechanism, and the information of the neighbor nodes is saved by constructing a set of potential neighbor nodes.
7. The vehicle ad hoc network clustering method based on link reliability as claimed in claim 1, wherein the cluster head selection and cluster formation candidates are vehicle nodes filtered by a preprocessing mechanism of a neighbor sampling method, and the neighbor sampling method is based on link lifetime.
8. The method according to claim 1, wherein the cluster maintenance comprises cluster head re-election, cluster fusion, and intra-cluster update.
9. The method as claimed in claim 8, wherein the cluster head re-election evaluates whether to accept the new vehicle node as the cluster head node by calculating a probability that a current state is replaced by a new state added to the new vehicle node.
10. The method according to claim 1, wherein the states of the vehicle nodes in the vehicular ad hoc network clustering algorithm comprise an initial state, a cluster head node state, a cluster member node state or a candidate cluster member state.
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