CN109862536A - Access method between the extensive more communities of car networking - Google Patents
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Abstract
In order to detect the connection between the more communities of extensive car networking and keep stable, the present invention provides access method between the more communities of extensive car networking, learning automaton theory is applied in the communication plan between the more communities of extensive car networking, information exchange and competition between learning automaton by being deployed in community's node, adaptively adjust the forwarding probability of different routings, to achieve the purpose that optimize network communication on the whole, it is access to promote extensive car networking network.
Description
The present invention is in " car networking community dynamic evolution method " filed in the inventors such as Cheng Jiujun on March 1st, 2019 (application
People: Tongji University, number of patent application: 201,910,155,584 2)) the further research and development of earlier application patent document, it should
First patent document can be considered a part of description of the invention.
Technical field
The present invention relates to car networking fields, and in particular to access method between the extensive more communities of car networking.
Background technique
Access is that network implementations interconnects one of most important characteristic, main connectivity and stabilization including in network
Property.Whether connectivity mainly solves point-to-point routing in network reachable；The emphasis of stability be then optimize network structure and
Routing policy is avoided because of the brings network efficiency problem such as congestion information and transmission delay.Below from the access side of car networking
Two emphasis of connectivity and stability are illustrated respectively in method.
(1) connectivity
The connection Journal of Sex Research of car networking is divided into qualitative analysis and quantisation metric analysis.Qualitative analysis is often referred to vehicle on road
The influence of distribution situation or car networking inherent characteristic to connectivity, and quantisation metric is then by comparing average data delay or to lose
The specific superiority and inferiority of the index studies difference such as packet rate connection strategy.Distribution of the vehicle on road is considered as Poisson distribution by Jin et al.,
The influence of traffic density and communication range to connectivity is studied in conjunction with the characteristic of road vehicle constraint.Further in vehicle in document
On the basis of node meets Poisson distribution, modeled using two-dimensional random graph model, qualitative and quantitative analysis traffic density
With the correlation degree of minimum wireless transmission distance, and accordingly in car networking key node position deployment guidance is provided.In addition,
The MCEGR method mentioned in chapter 1 be between in car networking community community connectivity compromise, but the problem is that
MCEGR is a double bounce method for routing, and community's scale is not very big, restricted application.
(2) stability
Stability is one of the key index for guaranteeing the fast-changing self-organizing network continual communication of this topological structure of car networking,
It is the access important component of car networking.In relation to the access scheme to be developed based on community, the stability of community is concern
Emphasis.Morales et al. proposes a kind of adaptive Community Clustering algorithm of In-vehicle networking, which moves according to vehicle node
The position of subsequent time vehicle node is predicted in track, present speed and position, road conditions etc., and combines current network topology
Carry out community's division with the network topology after prediction, it is contemplated that the trend of network change in future, improve community it is lasting when
Between and stability.
In conclusion these methods in terms of connectivity and stability the problem is that, when network size is larger and topological knot
When structure high dynamic changes, due to lacking adaptive routing, probably due to part connection is lost and cannot quickly be restored, lead to net
The access deficiency of network.In view of the above problems, the present invention is at " car networking community dynamic evolution method " filed on March 1st, 2019
(applicant: Tongji University, number of patent application: 2) 201910155584 study car networking dynamics community mechanism of Evolution real-time can obtain
To on the basis of car networking community structure, access side between a kind of more communities of extensive car networking based on learning automaton is proposed
Method, learning automaton theory is applied to the sensible Journal of Sex Research between the more communities of extensive car networking by this method, by being deployed in society
Information exchange and competition, adaptively adjust the forwarding probability of different routings, to reach from whole between the learning automaton of area's node
The purpose for optimizing network communication on body, it is access to promote car networking network.
Summary of the invention
Goal of the invention:
Research method of the present invention is complexity of interlocking for extensive car networking network objective reality road network, topological frequently variation, with
And communication protocol it is various phenomena such as the access problem of bring, using learning automaton theory, by being deployed between community's node
Information exchange and competition, corresponding excitation function and penalty are set, adaptively adjusts the forwarding probability of different routings, reaches
To Nash Equilibrium state, to realize the data transmission optimized in network on the whole, it is sensible to promote extensive car networking network
The purpose of property.
It is existing in terms of car networking community connectivity and stability the problem is that, when network size is larger and topological structure
When high dynamic changes, due to lacking adaptive routing, probably due to part connection is lost and cannot quickly be restored, lead to network
Connectivity is insufficient, it is also possible to because data aggregation leads to network congestion, cause part of nodes can not more than the traffic load upper limit
It works normally, causes network stabilization bad.Last conclusion is then: extensive car networking is as a kind of dynamic self-organization net
Network needs to establish the different routing forwarding probability adaptively adjusted and reaches Nash Equilibrium state, could promote car networking society
Access purpose inside area.
For this purpose, the present invention specifically gives following technical scheme realization: the access method in car networking community specifically includes following step
It is rapid:
The definition of step 1. relevant nature
Access method between the more communities of the extensive car networking of step 2.
The initialization of step 2.1 informational table of nodes and update
Step 2.2 community head node and gateway node screen
The forwarding behavior probability method of adjustment on LA is forwarded between step 2.3 community
Access routing algorithm between community more than step 2.4
Beneficial effect
Present invention aims at disclose a kind of to consider to provide one kind under extensive car networking high dynamic complex situations and be able to ascend vehicle
It networks the connection of more communities and stable access method.
On the basis of car networking community dynamic evolution method, (this part invention is see (inventors such as Cheng Jiujun were in 2019
" car networking community dynamic evolution method " (applicant: Tongji University, number of patent application 201910155584 filed in March 1
2) a kind of access method between more communities of extensive car networking), is given.Learning automaton theory is applied to vehicle by this method
Connected community, information exchange and competition, adaptively adjust different routings between the learning automaton by being deployed in community's node
Probability is forwarded, to achieve the purpose that optimize network communication on the whole, it is access to promote car networking network.
Subordinate list explanation
1 nodal information literary name section of table
2 node v of tablechCommunity between forward behavior probability vector table
Detailed description of the invention
Fig. 1 car networking community's gateway node and head node schematic diagram
The community Fig. 2 head node and gateway node screening process figure (i.e. 1 flow chart of algorithm)
Communication process schematic diagram between Fig. 3 car networking community
LA forwarding behavior probability adjustment algorithm flow chart (i.e. 2 flow chart of algorithm) is forwarded between the community Fig. 4
Access routing algorithm flow chart (i.e. 3 flow chart of algorithm) between the community Tu5Duo
Fig. 6 LA runs figure between car networking community
Fig. 7 TAPASCologne data set road topology figure
Fig. 8 PDR changes with traffic density to be compared
Fig. 9 PDR is compared with data package transmission velocity
Figure 10 E2ED changes with traffic density to be compared
Figure 11 E2ED is compared with data package transmission velocity
Figure 12 ROR changes with traffic density to be compared
Figure 13 ROR is compared with data package transmission velocity
Figure 14 is the method for the present invention flow chart
Specific embodiment
Specific implementation process of the invention is as shown in figure 14, including following 6 aspects:
1. relevant nature defines
2. informational table of nodes initialization and update
3. community's head node and gateway node screen
4. forwarding the forwarding behavior probability method of adjustment on LA between community
Access routing algorithm between the community ⑤Duo
6. emulation experiment and interpretation of result
①
Relevant nature definition
For the node in car networking community, the access scheme that the present invention uses will assign different roles for it, be respectively
Community's head node, community's gateway node and community's ordinary node, are defined as follows:
Define 1 community's cephalomere point set (CHSet): community CiHead node (CH) be the community in the biggish node of community's centripetal force
Set, if in community CiMeeting mathematic(al) representation there are node u is (1):
Wherein, η be head node selective factor B, general η take (0.75,1] in one value, community CiIn meet the section of above-mentioned condition
Point u is added into CiCHSet in.Node in CHSet is existing community CiThe interior preferable node of communication quality, in community
The node of CHSet is generally selected as relay node.
Define 2 community's gateway node collection (GWSet): community CiGateway node refer to the community and respectively its abut community attract
The maximum node of power.That is: if community CiWith CjIt is adjacent, then CiRelative to CjGateway node u meet mathematic(al) representation be (2):
ζ be gateway node selective factor B, general ζ take (0.9,1] in one value, community CiIn meet the node u of above-mentioned condition
It is added into CiRelative to CjGWSet in.If community CiThere are multiple adjacent communities, then CiMultiple gateway nodes are certainly existed, it will
These gateway nodes are added to CiGWSet in.Each gateway node leads to corresponding adjoining community is used for
Letter.Community's head node and community's gateway node are as shown in Figure 1.
From figure 1 it appears that the head node of community 1 and the connection of community's interior nodes are the closest, it is normally at community more
The position at center.In addition, the gateway node more than one of community 1, has gateway node relative to community 2 and community 3 respectively, and
Possible more than one.
It defines 3 community's ordinary nodes (CM): all can be described as community's ordinary node in addition to head node in a community.
Generally, due to car networking is the network of high dynamic variation, the role of each node can with itself movement with
Topology and signal intelligence variation and change, ordinary node, head node role may according to the demand of network-in-dialing and
It exchanges.
It defines 4 node connected probabilities (Node Connectivity Probability, NCP) and refers to that car networking interior joint is connected to
Credibility.
If node u is adjacent with node v and in respective range for wireless communication, their direct connected probability (Direct Node
Connectivity Probability, DNCP) be mathematic(al) representation (3):
Wherein, dist (u, v) indicates that the distance between node u and v, TR indicate the maximum communication radius of node.When between node
Distance when being greater than node maximum communication radius, the connected probability between node is 0；Otherwise, the connected probability meeting between node
Increase with the reduction of distance between node.
It, i.e., can be by other node configuration node communication paths, if this path between node u and v if two node indirect communications
It is expressed as NodePathi={ e1,e2,…,en, wherein e1=u, en=v, n > 2, n indicate the quantity of node on the access, then
Node u and v are in NodePathiOn node connected probability (Path Node Connectivity Probability, PNCP)
It is:
That is direct the tired of node connected probability of u and v communication path multiplies.Since there may be a plurality of node access between u and v
Diameter, between definition node u and v indirect inode connected probability (Indirect Node Connectivity Probability,
INCP) be connected probability on all node communication paths maximum value:
INCP (u, v)=max (PNCP (NodePathi)) (5)
To sum up, the node connected probability between definition node of the present invention is the maximum value in DNCP and INCP:
NCP (u, v)=max (DNCP (u, v), INCP (u, v)) (6)
It defines 5 community's connected probabilities (Community Connectivity Probability, CCP) and refers to two car networking communities
Between the credibility that is connected to.
If two car networking community CiWith CjIt is adjacent and all have gateway node be able to maintain the communication with other side community, then they directly
Connected probability (Direct Community Connectivity Probability, DCCP) meets mathematic(al) representation (7):
Wherein, u and v is respectively community CiAnd CjGateway node, two adjacent community CiAnd CjDirect connected probability is equal to their nets
The maximum value of the node connected probability of artis.
If two community's indirect communications, i.e. community CiAnd CjBetween there are community communication path CommunityPathi={ C1,
C2,…,Cm, wherein C1=Ci,C2=Cj, m > 2, m indicate the quantity of community on the access, then community CiAnd Cj?
CommunityPathiOn community's connected probability (Path Community Connectivity Probability, PCCP)
Meet mathematic(al) representation (8):
That is CiAnd CjThe tired of direct connected probability of community's communication path multiplies.Similarly, due to CiAnd CjBetween there may be a plurality of
Community's communication path defines community CiAnd CjBetween indirect communication probability (Indirect Community Connectivity
Probability, ICCP) be connected probability on all community's communication paths maximum value, meet mathematic(al) representation (9):
ICCP(Ci,Cj)=max (PCCP (NodePathi)) (9)
To sum up, it is the maximum in direct connected probability and maximum indirect communication probability that the present invention, which defines intercommunal connected probability,
Value meets mathematic(al) representation (10):
CCP(Ci,Cj)=max (DCCP (Ci,Cj),ICCP(Ci,Cj)) (10)
②
Informational table of nodes initialization and update
In the Web communication layer of car networking, there is an informational table of nodes on each node, the field which includes includes section
Point self ID, current time, speed, acceleration, position longitude and latitude, community's ownership, node role, affiliated community's head node ID
And ID of gateway node etc..It is specific as shown in table 1.
In table 1, node ID is the unique identification of the node in car networking, if for RSU be to be determined by the type of node itself,
Timestamp represents current time, and the nodes such as speed, acceleration and longitude and latitude essential information can be obtained by sensor.For section
Point community ownership, calculating process are as follows: initial time, each node need the node broadcasts into its radio signal propagation
Neighbor node probe messages (Neighbor node detection message, NNDM), the node for receiving NNDM needs to reply
Confirmation message may determine that node and neighbor node with the presence or absence of side, thus come apparent neighbor information and net by this process
Network topological structure.Hereafter, using car networking community dynamic evolution method, (this part invention see (inventors such as Cheng Jiujun in
" car networking community dynamic evolution method " filed on March 1st, 2019 (applicant: Tongji University, number of patent application:
201910155584 2)), to determine that node community belongs to.It not only include the essential information of node itself in NNDM message,
It further include the node adjacency table (Node Adjacency List, NAL) of community where the node, NAL is a two-dimensional array.
If community CiNode number is m, its NAL are as follows:
Wherein, neip,qCommunity C is indicated when=0iIn node vpWith vqBetween side is not present, it is on the contrary then indicate vpWith vqIt is direct
Connected probability.In community's merger process based on node similarity and the evolutionary process based on increment, exchanged between node
NAL, so that each node both knows about the node adjacency information of itself affiliated community.
After the community structure at current time determines, community's adjacency list of each community (Community Adjacency List,
CAL), i.e. the adjoining community information of community can be obtained the broadcast mode of node adjacency table and obtained by similar.
③
Community's head node and gateway node screen
After the community structure at current time determines, community's adjacency list of each community (Community Adjacency List,
CAL), i.e. the adjoining community information of community can be obtained the broadcast mode of node adjacency table and obtained by similar.Community's head node
Screening can refer to and define 1 content and realize that for specific steps as shown in algorithm 1, specific flow chart is as shown in Figure 2.
By the step in algorithm 1, the head node of community and gateway node will be screened out, and by the content of CHSet
It is stored in the informational table of nodes of each node, the foundation for subsequent access routing provides information support.
④
The forwarding behavior probability method of adjustment on LA is forwarded between community
For car networking society section communication, i.e. source node voriWith destination node vdesIt is located at different car networking communities, is led to
Letter process is broadly divided into three steps:
(1)voriThe gateway node GW of community where forwarding information to source node through society's intra-area communicationori；
(2) gateway node GWoriThe gateway node GW of community where information is forwarded to destination node by society's section communicationdes；
(3)GWdesDestination node v is forwarded information to through society's intra-area communicationdes。
Wherein, step (1) and (3) belong to society's intra-area communication.In step (1), if community gateway node GW is ordinary node v's
In communication range, then ordinary node directly forwards information to gateway node；If being unable to direct communication, due to community head node CH
Possess the routing of all nodes in community, therefore ordinary node first sends information to head node CH, then is transmitted to GWSet by CH
In suitable gateway node.Step (3) is the inverse process of step (1), and only locating community is different, is repeated no more here.Step
Suddenly (2) belong to society's section communication, and gateway node is the load bearing unit of society's section communication, play the role of the adjacent community of connection.On
The schematic diagram for stating process is as shown in Figure 3.
In Fig. 3, source community CoriWith target community CdesWhen establishing communication, CoriIn head node need judge next to which
A community forwards message, and forwards the messages to gateway node corresponding with the community.For this purpose, such as existing community is Ci,
Its head node vchBehavior vector table is forwarded between one group of community of upper maintenance, as shown in table 2.
It forwards behavior probability vector not refer to gateway node between the community in table 2, is because in next-hop CnextIn statement
Included corresponding gateway node.CPFrIndicate that in target community be Cp, next-hop community is CnextqForwarding probability.
Similarly, the value of PF can change with the progress of communication, and the process of change will be by environment to being deployed in community head node vchOn
The feedback mechanism of LA determines.The feedback of environment when in order to quantify society's section communication, define new scale community chance forwarding judge because
Sub (Community Opportunity to Forward Evaluation, COFE) meets mathematic(al) representation (12):
Wherein, CCP is community's connected probability, and RER and Delay respectively indicate community's dump energy and community's delay.η″,With
ψ " is the adjustment factor of NCP, RER and Delay respectively.
Similarly, it is deployed in vchCommunity between forwarding LA carve forwarding behavior number of vectors at the beginning and be set as l, LA forwards probability
It is initialized as:
That is t=0 forwards each forwarding probability on LA identical between community.Following instant selects the COFE of i-th of forwarding behaviori
Evaluation factors COFE is forwarded with the mean chance on the LAavgCompare, if COFEi≥COFEavg, then LA makes excitation to this behavior
Movement:
If COFEi≤COFEavg, then LA makes punishment movement to this behavior:
Wherein, ρ is excitation parameters, and ρ ' is punishment parameter.
In conclusion forward the forwarding behavior probability adjustment specific steps on LA as shown in institute's algorithm 2 between community, specific flow chart
As shown in Figure 4.
Algorithm 2 is the forwarding probability adjustment between LA is forwarded the community being deployed on each community's head node, whenever there is community
Between message forward when, these LA will according to previous moment COFE value to forwarding behavior probability vector be motivated or be punished.
⑤
Access routing algorithm between more communities
On the basis of algorithm 2, access method for routing between community is obtained, detailed step is as shown in algorithm 3, and specific flow chart is such as
Shown in Fig. 5.
In algorithm 3, adjacency list CAL is similar to NAL between community, and whether expression is adjacent between community.If community CiWith CjNo
It is adjacent thenIf adjacentValue be community CiWith CjDirect connected probability.In addition, message in order to prevent
The case where falling into endless loop or information drop-out in transmitting between community limits maximum community's forwarding jumping figure value as CHOPmaxIf
Jumping figure value K is more than CHOPmax, source community will forward again.
It forwards LA to be exchanged with each other data and competition in network communications between the community being deployed in each car networking community, passes through this
The operation of a little LA, the network of the car networking of high dynamic variation is access to be continued to optimize, LA operating condition between car networking community
As shown in Figure 6.
⑥
Emulation experiment and interpretation of result
(1) emulation experiment data and method
1) experimental data
In order to verify the correctness of method proposed by the present invention, experimental data range of choice of the present invention is wider, category of roads is more,
The bigger data set of the order of magnitude, i.e. TAPASCologne data set, dataset acquisition Cologne, Germany city 400 sq-km
(road topology figure is as shown in fig. 7, cover inner city section, suburb section with vehicular movement information for road information in range
And rural section), and generate the mobile trajectory data of the region all vehicles in 24 hours.
Present invention experiment will be joined using the track of vehicle data of 6:00~8:00 (am) period in TAPASCologne as vehicle
The foundation of community's evolution simulation experiment is netted, in the period, while the vehicle node moved on road is at most more than 8000
It is a, meet requirement of the present invention experiment to extensive car networking community experiment on evolution.
2) experimental method
Emulation experiment is on the basis of TAPASCologne data set, wherein SUMO emulator is still traffic simulation work
Tool, OMNET++ software and Veins frame are then still as network law.The present invention is in car networking community dynamic evolution
Method, (this part invention is see (" dynamic evolution side, car networking community filed in the inventors such as Cheng Jiujun on March 1st, 2019
Method " (applicant: Tongji University, number of patent application 2019101555842)) on the basis of, propose the vehicle based on learning automaton
The access method of connected community (CAVN-LA), by emulation experiment compare CAVN-LA relative to other algorithms (MCEGR with
AMACAD advantage), to verify the correctness of front Suo Ti car networking community dynamic evolution mechanism.The main net of emulation experiment
Network index is:
(a) destination node data packet number and source average packet delivery fraction (Packet delivery radio, PDR): are successfully reached
Node is sent to the ratio mean value of destination node data packet sum；
(b) average end-to-end delay (End-to-End delay, E2ED): the data packet that source node is sent reaches destination node institute
The mean value to take time；
(c) average routing cost rate (Routing overhead radio, ROR): detection is communicated with being building up to since routing
In the entire period completed, the data packet for finding and exchanging routing accounts for the ratio mean value of all data packets.
(2) interpretation of result
The simulation experiment result of the present invention is the average packet delivery fraction, average end-to-end delay, average road by comparing algorithms of different
By three kinds of network indexes such as overhead rate, and obtained under the conditions of node density and data packet transmission two kinds of experiment controls of rate respectively
's.It influences each other to control variable as far as possible, in the relationship of test network index and traffic density, the present invention takes another change
Amount is that data package transmission velocity is 0.3p/s；In test network index and the relationship of data package transmission velocity, another variable is taken
It is 0.05/meter that i.e. traffic density, which is traffic density, is illustrated in detail below.
(1) average packet delivery fraction PDR
Fig. 8 is the functional relation of PDR value and traffic density.It is clear that the PDR value of three kinds of algorithms is all with traffic density at positive
It closes, CAVN-LA and AMACAD algorithmic statement is very fast, and MCRGR convergence is slower.Wherein, CAVN-LA and AMACAD algorithm is close in vehicle
Degree is more stable greater than showing after 0.03/meter, this is because adaptive and Self-adjusting Mechanism has been all made of in both algorithms,
So that success rate and high stability that data packet is delivered.The amplitude of variation of MCRGR algorithm is larger, this is because the algorithm limits
Community scope is up to double bounce, and community's scale is smaller, shows in the biggish situation of traffic density preferably, for node Sparse-Field
Scape performance is general, but data packet delivery fraction of this method after traffic density is greater than 0.05/meter is close to proposed in this paper
CAVN-LA algorithm, this is because the evolution competition mechanism in MCRGR has similar place with CAVN-LA, under the dense scene of node
Performance is preferable.Generally speaking, the learning automaton mechanism in CAVN-LA algorithm keeps its adaptive self-adjusting ability stronger, PDR
There is preferable performance under the sparse and dense scene of node.
Fig. 9 is the functional relation of PDR value and data package transmission velocity.As can be seen that the PDR value of three kinds of algorithms is sent out with data packet
Transmission rate increases and reduces, because of being continuously increased with data package transmission velocity, in car networking network, data are gradually dense, number
Increase according to a possibility that collision, data packet, which delivers successful ratio, to be reduced.The wherein PDR of CAVN-LA and AMACAD algorithm
Value variation is still relatively stable, and only the highest PDR ratio AMACAD of CAVN-LA will be higher by 10% or more.The highest PDR of MCRGR
Be not much different with CAVN-LA, close to 90%, but data package transmission velocity be greater than 0.8 after, the performance of MCRGR sharply under
Drop, and CAVN-LA is still showed well, this is because the number of each community's head node and gateway node may not in the algorithm
Only one, and the mechanism of learning automaton plays the role of a load balancing.
(2) average end-to-end delay E2ED
Figure 10 is the relational graph of E2ED and traffic density variation.It can be seen from the figure that the E2ED value of three kinds of algorithms is close with vehicle
The increase of degree and reduce, this is because the network connectivty between car networking node increases when traffic density increases, carry forwarding
Number reduce, so that average retardation be made to reduce.Wherein, the average retardation of CAVN-LA is minimum, but when traffic density is greater than
When 0.055/meter, the average retardation of MCRGR algorithm and being reduced to is not much different with CAVN-LA algorithm.In addition, AMACAD
The E2ED value variation of algorithm is equally also more stable, but since the adaptive ability of its routing adjustment is insufficient, thick in node
In the case where close, average retardation is also slightly above other two kinds of algorithms.
Figure 11 is the relational graph of E2ED and data package transmission velocity variation.The E2ED value of three kinds of access routing algorithms is with number
The trend for becoming larger according to the increase of packet sending speed, and becoming larger is more and more big, this is because with data package transmission velocity
Increase, the load of network becomes larger so that subsequent data packet can enter the waiting sequence of forward node, therefore being averaged for network is prolonged
It can become larger late.When data package transmission velocity is 0.005p/s, the E2ED value of three kinds of methods is not much different, and may each be about 0.2s, but
When data package transmission velocity is 0.06p/s, the performance of MCRGR algorithm has decreased sharply to 6s, will beyond CAVN-LA algorithm
Nearly 2.3s.Therefore, on the whole, the average retardation of CAVN-LA algorithm is more slightly lower than other two kinds of algorithms, there is some superiority.
(3) average routing cost rate ROR
Figure 12 is the function relation figure that ROR changes with traffic density.It can be seen that increase of the ROR of three kinds of algorithms to traffic density
There is certain growth, wherein the ROR value highest of AMACAD algorithm, this is because the algorithm is used to establish the data of car networking community
Packet switch mechanism takes compared with large overhead, and with the increase of traffic density, this routing cost can constantly increase.CAVN-
The ROR value of LA algorithm comes second, this is because the Competition Evolutionary mechanism in the algorithm, needs a certain number of control messages,
The exchange of excitation table is updated and punished to the dynamic of head node and gateway node collection.MCEGR algorithm is to traffic density
Variation be not it is very sensitive, which is to establish to be, and its double bounce community determines on the basis of being predicted according to node location
The accounting for controlling message is lower, is maintained at 5% or so.
Figure 13 is the function relation figure that ROR changes with data package transmission velocity.Can be found out in Figure 12 when data packet sends speed
When rate is 0.3p/s, traffic density is 0.015/meter, CAVN-LA algorithm is identical with the ROR of MCEGR algorithm, and this point is being schemed
Also it is proved in 13.In addition, the ROR value of AMACAD algorithm be still it is highest in three, with the increasing of data package transmission velocity
Greatly, the disadvantage in terms of the algorithm routing cost is more and more obvious.All in all, the ROR ratio MCEGR of CAVN-LA algorithm is slightly higher, compared with
AMACAD wants low 2% or so, and performance of the comprehensive algorithm in terms of PDR and E2ED, the minor cost of ROR exchanges for access
The prompt of performance is worth.
Innovative point
Innovative point: being based on car networking community dynamic evolution method, (" vehicle filed in the inventors such as Cheng Jiujun on March 1st, 2019
Connected community's dynamic evolution method " (applicant: Tongji University, number of patent application: 201,910,155,584 2)), certainly using study
Corresponding excitation function and penalty is arranged by the information exchange and competition being deployed between community's node in motivation technology, from
The forwarding probability for adapting to adjust different routings is realized access between the more communities of extensive car networking.
Extensive car networking network objective reality road network is staggeredly complicated, the characteristics such as the frequent variation of topology and communication protocol multiplicity,
Largely give extensive car networking network-in-dialing and stabilized zone next huge challenge.The present invention will be in view of the above problems, will learn
It practises automaton theory to be applied in the communication plan between the more communities of extensive car networking, by being deployed in the study of community's node certainly
Information exchange and competition, adaptively adjust the forwarding probability of different routings between motivation, so that it is logical to reach optimization network on the whole
It is access to promote extensive car networking network for the purpose of letter.
Specification subordinate list
Table 1
Table 2
Claims (6)
1. access method between the extensive more communities of car networking, specifically comprises the following steps:
The definition of step 1. relevant nature
Access method between the more communities of the extensive car networking of step 2.
The initialization of step 2.1 informational table of nodes and update
Step 2.2 community head node and gateway node screen
The forwarding behavior probability method of adjustment on LA is forwarded between step 2.3 community
Access routing algorithm between community more than step 2.4.
2. access method between the extensive more communities of car networking as described in claim 1, which is characterized in thatThe relevant nature Definition, comprising steps of
Define 1 community's cephalomere point set (CHSet): community CiHead node (CH) be the community in the biggish node of community's centripetal force
Set, if in community CiMeeting mathematic(al) representation there are node u is (1):
Wherein, η be head node selective factor B, general η take (0.75,1] in one value, community CiIn meet the section of above-mentioned condition
Point u is added into CiCHSet in.Node in CHSet is existing community CiThe interior preferable node of communication quality, in community
The node of CHSet is generally selected as relay node.
Define 2 community's gateway node collection (GWSet): community CiGateway node refer to the community and respectively its abut community attract
The maximum node of power.That is: if community CiWith CjIt is adjacent, then CiRelative to CjGateway node u meet mathematic(al) representation be (2):
ζ be gateway node selective factor B, general ζ take (0.9,1] in one value, community CiIn meet the node u quilt of above-mentioned condition
C is addediRelative to CjGWSet in.If community CiThere are multiple adjacent communities, then CiMultiple gateway nodes are certainly existed, by this
A little gateway nodes are added to CiGWSet in.Each gateway node is communicated corresponding adjoining community is used for.
It defines 3 community's ordinary nodes (CM): all can be described as community's ordinary node in addition to head node in a community.
Generally, due to car networking is the network of high dynamic variation, the role of each node can with itself movement with
Topology and signal intelligence variation and change, ordinary node, head node role may according to the demand of network-in-dialing and
It exchanges.
It defines 4 node connected probabilities (Node Connectivity Probability, NCP) and refers to that car networking interior joint is connected to
Credibility.
If node u is adjacent with node v and in respective range for wireless communication, their direct connected probability (Direct Node
Connectivity Probability, DNCP) be mathematic(al) representation (3):
Wherein, dist (u, v) indicates that the distance between node u and v, TR indicate the maximum communication radius of node.When between node
Distance when being greater than node maximum communication radius, the connected probability between node is 0；Otherwise, the connected probability meeting between node
Increase with the reduction of distance between node.
It defines 5 community's connected probabilities (Community Connectivity Probability, CCP) and refers to two car networking societies
The credibility being connected between area.
If two car networking community CiWith CjIt is adjacent and all have gateway node be able to maintain the communication with other side community, then they directly
Connected probability (Direct Community Connectivity Probability, DCCP) mathematic(al) representation (4):
Wherein, u and v is respectively community CiAnd CjGateway node, two adjacent community CiAnd CjDirect connected probability is equal to their nets
The maximum value of the node connected probability of artis.
3. access method between the extensive more communities of car networking as described in claim 1, which is characterized in thatAt the beginning of informational table of nodes Beginningization and update, comprising steps of
In the Web communication layer of car networking, there is an informational table of nodes on each node, the field which includes includes section
Point self ID, current time, speed, acceleration, position longitude and latitude, community's ownership, node role, affiliated community's head node ID
And ID of gateway node etc..
4. access method between the extensive more communities of car networking as described in claim 1, which is characterized in thatCommunity's head node with Gateway node screening, comprising steps of
After the community structure at current time determines, community's adjacency list of each community (Community Adjacency List,
CAL), i.e. the adjoining community information of community can be obtained the broadcast mode of node adjacency table and obtained by similar.Community's head node
Screening with community's gateway node, which can refer to, to be defined 1 and defines 2 content to realize.
5. access method between the extensive more communities of car networking as described in claim 1, which is characterized in thatLA is forwarded between community On forwarding behavior probability method of adjustment.Comprising steps of
For car networking society section communication, i.e. source node voriWith destination node vdesIt is located at different car networking communities, is led to
Letter process is broadly divided into three steps:
(1)voriThe gateway node GW of community where forwarding information to source node through society's intra-area communicationori；
(2) gateway node GWoriThe gateway node GW of community where information is forwarded to destination node by society's section communicationdes；
(3)GWdesDestination node v is forwarded information to through society's intra-area communicationdes。
Wherein, step (1) and (3) belong to society's intra-area communication.In step (1), if community gateway node GW is ordinary node v's
In communication range, then ordinary node directly forwards information to gateway node；If being unable to direct communication, due to community head node CH
Possess the routing of all nodes in community, therefore ordinary node first sends information to head node CH, then is transmitted to GWSet by CH
In suitable gateway node.Step (3) is the inverse process of step (1), and only locating community is different, is repeated no more here.Step
Suddenly (2) belong to society's section communication, and gateway node is the load bearing unit of society's section communication, play the role of the adjacent community of connection.
Source community CoriWith target community CdesWhen establishing communication, CoriIn head node need judge next to which community turn
Message is sent out, and forwards the messages to gateway node corresponding with the community.
6. access method between the extensive more communities of car networking as described in claim 1, which is characterized in thatIt is sensible between more communities Property routing algorithm:
。
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247826A (en) * | 2019-07-10 | 2019-09-17 | 上海理工大学 | A kind of point to point network continuity testing method |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070087756A1 (en) * | 2005-10-04 | 2007-04-19 | Hoffberg Steven M | Multifactorial optimization system and method |
| CN101808382A (en) * | 2010-01-20 | 2010-08-18 | 西安电子科技大学 | Data communication method of wireless sensor network |
| US20110134840A1 (en) * | 2009-12-08 | 2011-06-09 | Electronics And Telecommunications Research Institute | Location based vehicle multihop protocol unicast apparatus and routing method using the apparatus |
| CN102917372A (en) * | 2012-10-18 | 2013-02-06 | 北京理工大学 | Internet of vehicles hierarchical model design method orienting to multi-scene data exchange |
| CN103079270A (en) * | 2013-02-05 | 2013-05-01 | 中国电子科技集团公司电子科学研究院 | Method for sensing aggregation of mobile nodes on basis of wireless positioning |
| CN103781148A (en) * | 2014-02-25 | 2014-05-07 | 重庆邮电大学 | Stable clustering routing method based on link perception in vehicle-mounted self-organizing network |
| CN105792311A (en) * | 2016-02-29 | 2016-07-20 | 重庆邮电大学 | Routing method for internet of vehicles based on user activity area model |
| KR101700588B1 (en) * | 2015-09-15 | 2017-02-13 | 가톨릭관동대학교산학협력단 | VANET system using a Mutual Authentication Scheme and Black Hole detection method using thereof |
| CN107509229A (en) * | 2017-08-03 | 2017-12-22 | 华南理工大学 | A kind of car networking chance method for routing calculated based on vehicle node centrality |
| CN108712287A (en) * | 2018-05-22 | 2018-10-26 | 同济大学 | VANET community discovery methods based on node similarity |
| CN108881016A (en) * | 2018-08-30 | 2018-11-23 | 同济大学 | The polygonal colour sorting community load-balancing algorithm of car networking self-organizing network |
| CN109302696A (en) * | 2018-08-30 | 2019-02-01 | 同济大学 | The polygonal colour sorting Community Clustering method of car networking self-organizing network |
-
2019
- 2019-03-07 CN CN201910171832.2A patent/CN109862536B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070087756A1 (en) * | 2005-10-04 | 2007-04-19 | Hoffberg Steven M | Multifactorial optimization system and method |
| US20110134840A1 (en) * | 2009-12-08 | 2011-06-09 | Electronics And Telecommunications Research Institute | Location based vehicle multihop protocol unicast apparatus and routing method using the apparatus |
| CN101808382A (en) * | 2010-01-20 | 2010-08-18 | 西安电子科技大学 | Data communication method of wireless sensor network |
| CN102917372A (en) * | 2012-10-18 | 2013-02-06 | 北京理工大学 | Internet of vehicles hierarchical model design method orienting to multi-scene data exchange |
| CN103079270A (en) * | 2013-02-05 | 2013-05-01 | 中国电子科技集团公司电子科学研究院 | Method for sensing aggregation of mobile nodes on basis of wireless positioning |
| CN103781148A (en) * | 2014-02-25 | 2014-05-07 | 重庆邮电大学 | Stable clustering routing method based on link perception in vehicle-mounted self-organizing network |
| KR101700588B1 (en) * | 2015-09-15 | 2017-02-13 | 가톨릭관동대학교산학협력단 | VANET system using a Mutual Authentication Scheme and Black Hole detection method using thereof |
| CN105792311A (en) * | 2016-02-29 | 2016-07-20 | 重庆邮电大学 | Routing method for internet of vehicles based on user activity area model |
| CN107509229A (en) * | 2017-08-03 | 2017-12-22 | 华南理工大学 | A kind of car networking chance method for routing calculated based on vehicle node centrality |
| CN108712287A (en) * | 2018-05-22 | 2018-10-26 | 同济大学 | VANET community discovery methods based on node similarity |
| CN108881016A (en) * | 2018-08-30 | 2018-11-23 | 同济大学 | The polygonal colour sorting community load-balancing algorithm of car networking self-organizing network |
| CN109302696A (en) * | 2018-08-30 | 2019-02-01 | 同济大学 | The polygonal colour sorting Community Clustering method of car networking self-organizing network |
Non-Patent Citations (2)
| Title |
|---|
| JIUJUN CHENG: "Routing in Internet of Vehicles:A Review", 《IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS》 * |
| 肖晶: "基于社会网络理论的车载自组织网络路由协议及算法研究", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247826A (en) * | 2019-07-10 | 2019-09-17 | 上海理工大学 | A kind of point to point network continuity testing method |
| CN110247826B (en) * | 2019-07-10 | 2022-03-25 | 上海理工大学 | Point-to-point network connectivity test method |
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