CN109302696B

CN109302696B - Multi-role classification community clustering method for self-organizing network of Internet of vehicles

Info

Publication number: CN109302696B
Application number: CN201811001452.6A
Authority: CN
Inventors: 程久军; 米浩东; 黄震华; 陈敏军; 余润身
Original assignee: Tongji University
Current assignee: Tongji University
Priority date: 2018-08-30
Filing date: 2018-08-30
Publication date: 2021-04-30
Anticipated expiration: 2038-08-30
Also published as: CN109302696A

Abstract

The existing community clustering method aiming at the Internet of vehicles mostly adopts the position of the vehicles at the future time such as the current speed, the driving direction and the like to estimate the time length of the connection between the nodes in the future, and the time length is used as one of clustering bases to improve the community stability. However, the position of the vehicle at the future moment is influenced by multiple factors, and the accuracy of the estimated communication connection time is low, so that the communities in the Internet of vehicles have the characteristics of short life cycle and rapid change of the attribution of the node communities. Meanwhile, the existing routing protocol of the car networking community takes key nodes in the community as main nodes for forwarding, so that the problem of overhigh load of the key nodes is caused. The invention provides a multi-role classification community clustering method of an Internet of vehicles self-organizing network aiming at the problems, and the method considers the position of a vehicle at a future moment in the community clustering process and refines role distribution in the community. The community attribute and community node role definitions comprise community attributes and community node roles. The community clustering and role distribution method comprises community formation and community maintenance.

Description

Multi-role classification community clustering method for self-organizing network of Internet of vehicles

Technical Field

The invention relates to the field of car networking.

Background

Different from the traditional community clustering, the moving speed of the vehicle nodes in the Internet of vehicles is high, and the topological relation among the nodes is changed rapidly. The traditional community clustering method is applied to the Internet of vehicles, and has the defects of short community life cycle and low stability.

In a community clustering method designed for the Internet of vehicles, researchers propose that the current position, the current speed and the end point position of each node of a node are comprehensively considered in community clustering, and the topological relation of a vehicle in a future period of time is estimated, so that the topological relation is used as a clustering basis to prolong the survival time of a community. According to the method, after the head nodes of the two communities enter a communication area, the community combination is carried out after a period of time is delayed until the head nodes of the communities keep a relatively stable communication state, so that frequent combination and splitting of the communities are reduced, and the community stability is improved. There is a document that the moving direction of a vehicle is added into a clustering basis, and the number of neighbor nodes and an untrusted factor are integrated to be used as a basis of community clustering. The method discussed above simply selects several of the most obvious vehicle location influencing factors, and discards a great deal of traffic information that may influence the future vehicle location. When the influence factors are utilized for community clustering, the stability of the community is not improved enough, and the clustered community still has the characteristics of short life cycle and fast node attribution change.

Disclosure of Invention

The research method of the invention is based on the existing community clustering method aiming at the Internet of vehicles, and mainly adopts the current speed, the driving direction and the like to estimate the position of the vehicle at the future time to judge the time length of the connection between the future nodes, and the time length is taken as one of clustering bases to improve the community stability. Based on a vehicle position prediction model (inventor of Chengdu and the like applies for a position prediction model construction method based on deep learning vehicle driving influence factors in a vehicle networking complex network on 2017, 8, 16) (applicant: Tongji university, patent application No. 2017107029220, No. 107609633A, 2018, 01, 19, 2018), vehicle body attributes, road information, driving environment and other factors influencing vehicle driving are comprehensively considered, a deep learning technology is combined, the relation between the vehicle driving influence factors and the vehicle position is mined, a prediction model of the vehicle position is provided), the vehicle future time position is considered in a community clustering process, and role distribution is refined in a community, so that community stability is improved, key node load is balanced, and data transmission distortion is reduced.

The invention provides the following technical scheme:

a multi-role classification community clustering method of a self-organizing network of the Internet of vehicles is characterized by comprising two parts,

one, community attribute and community node role definition

Step 1, community attribute;

and 2, the community node has the role.

Second, community clustering and role distribution method

Step 1, forming a community;

and 2, community maintenance.

A multi-role classification community clustering method under the scene of a self-organizing network of the Internet of vehicles is characterized by comprising two parts,

one, community attribute and community node role definition

Step 1.1, theCommunity attributes, defined as follows:

VANET is abstracted into the structure of a weighted undirected graph. The vehicle nodes serve as points in the undirected graph, and the wireless connections between vehicles serve as edges between the points. The undirected graph with weight is G ═ V_G,E_G). Wherein V_G＝{ve₁,ve₂,…ve_kDenotes the set of vertices, ve_kRepresenting vertex k. E_G＝{e₁,e₂,…e_jDenotes an edge set, e_jRepresenting edge j. The communities are represented by vertex sets and edge sets, and are abstracted into a G subgraph form and are marked as

If two vehicles are within the transmission range of each other, an edge is considered to exist between the nodes abstracted by the two vehicles.

(1) Definition 1 vehicle direct connectivity factor trf (trassmision factor): representing the reliability of the connection between the two vehicle nodes, satisfying equation (2).

Where tr (transmission range) represents the maximum transmission range of vehicle communication. dist_t(ve_i,ve_j) Representing the distance between vehicle i and vehicle j at time t. When the distance between the vehicles is greater than the maximum transmission range, the TRF is 0, indicating that there is no connection between the two vehicle nodes. Reflected on the topology map, i.e. there is no edge between two nodes. When the distance between the vehicles is less than or equal to the maximum transmission range, the TRF is inversely related to the distance between the vehicles. The closer the distance, the larger the TRF, the higher the reliability of the connection between two vehicle nodes, and the closer the connection, the greater the weight reflected to the upper side of the topological graph.

(2) Defining 2 neighbor nodes: if the vehicle A and the vehicle B satisfy TRF (ve)_A,ve_N)>0, the A and the B are called as neighbor nodes. Reflected in the topological graph, i.e. ve_AAnd ve_BThere is an edge in between.

The node neighbor connection centrality is defined to represent the number of current neighbor nodes of the vehicle and the closeness of the connection between the vehicle and the neighbor nodes.

(3) Define 3 Neighbor Connectivity Centrality (NCC): representing the sum of the direct connectivity factors of the node and the neighboring nodes. Will ve_iThe NCC value of the node at the time t is recorded as C_i,tThen, there are:

wherein the NS_iA set of neighbor nodes representing inodes. The larger the NCC, the more reliable the connection between the node and its surrounding nodes is, and the closer the connection is.

(4) Define 4 Expected Neighbor Connection Centrality (ENCC): representing a weighted average of the NCC values of the nodes for a future period of time, starting from the current time instant. Node ve at time t_iHas an ENCC value of

Then there are:

where DTS denotes a set of time intervals { dt | dt ═ 0, Δ t,2 Δ t,3 Δ t, … }, and WS denotes a set of weights { w | w ═ w }₁,w₂,…}，w_kRepresenting the weight corresponding to the NCC value at the moment of t + (i-1) delta t. The larger the ENCC value, the more reliable the connection of the vehicle to the surrounding nodes in the future period of time represented by the DTS, and the tighter the connection.

(5) Define 5 Community Neighbor Connection Centrality (CNCC): representing the sum of the direct connectivity factors of the node to the nodes in the specified community at the current time. Let t time ve_iNode pair community COM_kCNCC value of

Then there is

Wherein

Is denoted ve_iCOM (component object model) of node-in-community_kA set of neighboring nodes in (1). CNCC represents the quality of direct connection of the vehicle node to a community population. The bigger the CNCC value is, the more the COM value is, the more the node is currently connected with the community_kThe higher the overall quality of the direct connection, the tighter the connection.

(6) Define 6 expected community neighbor connection centrality (ENC): representing a weighted average of the CNCC values of the designated community by the node some time after the current time. Let t time ve_iNode pair community COM_kThe ENC value of (A) is recorded as

Is provided with

The larger the ENC value is, the more the COM value is, the COM value is with the community in the future_kThe higher the overall quality of the direct connection, the tighter the connection. The influence of the CNCC value at a certain moment can be expanded by adjusting the weight of the CNCC at each time point to focus on considering the CNCC value at the moment.

(7) Define 7 node remaining load capacity (AWL): indicating the buffer space remaining for the node to forward data at the current time. Will ve_iThe AWL value of the node at the time t is recorded as AWL_i,t. At time t, to ve_iNode transmission greater than AWL_i,tWill cause the packet to be lost.

Step 1.2 theCommunity node role definition

In order to distinguish the positions of different nodes in the community, the positions of the nodes in the community and the contribution degrees of the nodes in the Internet of vehicles routing are represented. The car networking community clustering model may give different role definitions to nodes in the community. Generally, a community has at least one head node (CH) and several member nodes (CMs). The head node in the community manages various information of the community, such as a community node set, the position of each node in the community, a routing table and the like. In the process of community evolution, a head node can often decide whether a node which is not the community can join the community. Because the direct connectivity of the head node is high, the communication quality is good, and various important information in the community is stored, the head node is often regarded as an important forwarding node in the routing protocol of the Internet of vehicles community.

The invention defines a head node waiting node and a gateway node waiting node for balancing loads of the head node and the gateway node, and divides node roles in a community into five classes, namely the head node, the gateway node, the head node waiting node, the gateway node waiting node and a common member node. The role of a node that is not included in the community is defined as a free node.

(1) Define 8 head node (CH): the node with the highest ENC value in the community. Is provided with

Then node ve_iIs considered to be in the future for a period of time

The connection quality is best in the intra-community. The node is selected as COM_kThe CH node of (1). And if a plurality of nodes with the highest ENC value exist, selecting the node with the lowest number as the CH node.

(2) Define 9 head node waiting node (BCH): the nodes with relatively high degree of center are adjacent to the expected community in the community. Assume COM for community_kIn other words, the CH node is ve_hThen, the BCH node of the community needs to satisfy:

h represents the number of the CH node. Where δ is a control factor for the number of BCH nodes selected. At the beginning of community formation, the load of data transmission of the CH node and the BCH node is low, δ can be set to a large value, the number of the BCH nodes is reduced, the connection quality of the selected BCH node in the community is enabled to be closer to the CH node, and therefore the forwarding characteristic of the BCH node is enabled to be closer to the CH node. With the aggravation of the data packet forwarding task in the community, when both the CH node and the selected BCH node reach a very high data load, δ can be appropriately reduced, and more BCH nodes are selected to assist in data forwarding.

(3) Defining 10 Community COM_kTo community COM_lGateway node set (GWS): defined as set GWS_k,lAnd satisfies the following conditions:

namely Community COM_kTo community COM_lAll nodes of the gateway node set of (a) belong toCommunity COM_kAnd is connected with the community COM_lSome or all of the nodes in (1) are directly connected.

(4) Defining 11 Community COM_kTo community COM_lGateway node GW of_k,l: defined as set GWS_k,lMiddle-to-community COM_lNode with the largest ENC value. I.e. if ve_i∈GWS_k,lThen, it needs to satisfy:

if GWS is_k,lCOM in community_lIf the number of the nodes with the maximum number of the ENCs is multiple, the node with the lowest number is selected as the community COM_kTo community COM_lA gateway node (GW).

(5) Defining 12 Community COM_kTo community COM_lGateway node waiting node set BGWS_k,l: is defined as GWS_k,lRemoving gateway node GW_k,lAll nodes other than that, i.e.

BGWS_k,l＝{ve_i|ve_i≠GW_k,l,ve_i∈GWS_k,l} (11)

BGWS_k,lThe node in (1) is defined as a community COM_kTo community COM_lGateway node waiting node BGW_k,l。

Common member nodes (CMs) refer to all other community nodes except CH, BCH, GW, and BGW nodes in the community. The CM node conforms to the following two characteristics:

● CM node and single hop neighbor nodes that are community CH nodes. Namely for community COM_kThe CH node is CH_kThen CM node

And CH_kThere must be an edge e between_j,

● pairsAt node CM_iThe community of which is COM_kThen equation (12) is satisfied.

Nodes that do not belong to any community are defined as free nodes (SN).

II,Community clustering and role distribution method

The clustering of the communities in the Internet of vehicles is a process of dividing nodes in the Internet of vehicles into different communities. The invention divides the process of community clustering into two stages of community formation and community maintenance.

In the initialization stage of the self-organizing network of the Internet of vehicles, each vehicle node is initialized to be an SN node. After that, whether in the community formation phase or the community maintenance phase, the node broadcasts heartbeat control (HB) data packets to the neighbor nodes periodically. The HB data packet carries state information of the node, including the current position of the node, the future positions of 1s, 2s and 3s obtained by the node through prediction based on a vehicle position prediction model, the community to which the node belongs, the node ENCC value, the node ENC value, the node AWL value and the like. All nodes maintain a neighbor information table neighbor Table for calculating and comparing index data of neighbor nodes, such as ENCC and ENC. The individual contents of the information table are shown in table 1. The BEAT _ LENGTH in the table indicates the time interval between two adjacent HB packet transmissions. The neighbor node and ve are considered as if the HB data packet of longer time is missing_iThe node is disconnected and its information is removed from the neighbor information table.

Step 2.1 Community formation

Community formation begins with election of the community CH node. And when the node updates the self ENCC value, comparing the self ENCC value with the ENCC value of the neighbor node, thereby finding out the node with the maximum ENCC value. The node having the largest ENCC value is suitable to be selected as the CH node. And when a plurality of nodes with the maximum ENCC value exist, selecting the node with the minimum ID value as the CH node. And after the CH node is selected, marking the ID of the new community as the ID of the CH node, and enabling the neighbor node to know the establishment of the new community through an HB data packet broadcasted by the CH node. And if the neighbor node is the SN node, directly joining the community and informing the CH node in a mode of joining a community request (JC) data packet. If the neighbor node belongs to other nodes, whether the neighbor node is suitable for being added into a new community needs to be judged, and details are given in a community maintenance stage according to the judgment. And the CH node updates the community member table according to the received JC data packet. And if the JC data packet represents the request to join the community, adding the JC data packet sending node into a community member table. And if the JC data packet requests to join other communities, the node sending the data packet is moved out of the community member table. After several iterations, the community gradually tends to a relatively stable state. At this point, the process of community formation is completed.

Step 2.2 Community maintenance

In the community maintenance phase, the conditions of dynamic joining or leaving of the community by the nodes and merging, splitting and extinction of the community need to be processed. Meanwhile, the role distribution of the BCH, GW and BGW nodes is also carried out in the community maintenance phase.

(a) Updating node community attribution, eliminating community, merging and splitting

At this stage, the problem of node community attribution change needs to be handled. When the node receives the HB data packets broadcasted by the neighbor node, the time length of the connection between the node and the neighbor node is estimated according to the speed, the current position and the positions at the future time of 1s, 2s and 3s, and the information table of the neighbor node is updated.

After the neighbor node information table is updated, if the node finds that a new CH node appears in the neighbor node, whether the CH node is more suitable to be used as the CH node than the current community CH node is judged. Suppose node ve_iReceive ve_hTransmitted HB packets of which ve_hIs a newly appeared CH node in the neighbor nodes. Here, an improvement is made to the testclusterierheadchange algorithm (classical algorithm, commonly used for comparison experiments) in the MDMAC method (classical algorithm, commonly used for comparison experiments). Node ve_hThe following five criteria are satisfied to be considered more suitable for doing ve_iThe head node of (2):

6)ve_hthe node is the CH node of the community in which the node is positionedPoint;

7) the ENCC value satisfies

8)ve_hAnd ve_iIs sufficiently long;

9)ve_iand ve_hThe included angle of the speed between the two is small enough;

10) suppose ve_iThe community is COM_m，ve_hThe community is COM_nThen the ENC value needs to be satisfied

Meeting these criteria guarantees ve_hThe nodes have better direct connectivity, and ve is ensured_iNode and ve_hThe communities in which the nodes are located are more closely related. At the same time ensure ve_hAnd ve_iHave a longer time connection between them, can avoid ve_iFrequently joining and leaving communities.

If ve_hMore suitable as CH node, then ve_iSelectively add ve_hThe community in which the user is located. ve_iThe following operations are carried out according to the role of the user:

3) when ve_iWhen not a CH node, ve_iNotification of ve by broadcasting JC packets_hJoin the community. And notify the original community CH node ve_iLeaving the original community, and completing the attribution change of the node community;

4) when ve_iWhen it is a CH node, ve_iNotification of ve by broadcasting JC packets_hJoin the community. And other nodes in the community are informed, and the original community disappears. Other nodes within the community become SN nodes. And then according to the received HB data packets of other CH nodes, selecting to join other communities to complete the combination of the communities. Or self-electing to be a new community CH node, attracting surrounding nodes to join, and completing the division of the community.

Therefore, the node can complete the dynamic change of the node community attribution, the extinction of the community, the splitting and the combination according to the given rule.

(b) BCH, GW and BGW node role allocation

The community maintenance phase also needs to solve the role allocation problem of BCH, GW and BGW nodes. The CH and BCH nodes maintain the same community member list. And the CH and BCH nodes respectively maintain a gateway information table according to the updated information of the GW and the BGW nodes in the neighbor nodes. And the CH node maintains a community member list and knows the community status of each node in the community. And common nodes of the community do not have a community member list, so that the status of each node in the community cannot be known. Therefore, to select a node having a similar community status as the CH node as a BCH node, the BCH node is designated by the CH node. And other nodes in the community can know the adjacent community and can calculate the ENC value of the adjacent community. Therefore, the GW and BGW nodes are self-elected by each node in the community and inform the result to the CH node and the adjacent BCH node.

The BCH node is more suitable to be used as a BCH node according to the size of the ENC value and the closer to the ENC value of the CH node.

And selecting the GW and the BGW nodes according to the ENC value of the adjacent community. Suppose COM_iThere are 5 nodes and COM in the community_jNodes in the community are directly connected. The 5 nodes are represented as<ve₁,ve₂,ve₃,ve₄,ve₅>. It is to community COM_jThe ENC value of (A) is shown in Table 2.

To COM_jMaximum ve of community ENC₃The node is selected as the community COM_iTo community COM_jGW node of (1), the remaining 4 nodes being selected as community COM_iTo community COM_jThe BGW node of (1). The GW is distinguished from the BGW node only at the CH and BCH nodes because the gateway node tables of the community are maintained only at the CH and BCH nodes. In the self-election process of the gateway node, the nodes all consider themselves to be the BGW nodes.

The CH and BCH nodes need to maintain a community membership list that includes a CH node list (only one CH node in the list), a BCH list, a GW/BGW list, and a CM list. The CH node list, the BCH list and the GW/BGW list are collectively called a key node member list. In the process of choosing BCH and GW/BGW, the CH node and the corresponding BCH node update the member list of the key nodes according to the choosing result. After the CM node joins the community, the CH node and the corresponding BCH node update the CM list. And when the member node in the community leaves the community, the CH node and the BCH node remove the corresponding member, and corresponding new role selection is performed according to the role of the removed member. The member nodes leave the community can be divided into the following two cases:

1) the member node joins other communities and actively informs the CH node and the corresponding BCH node. At this time, the CH node and the BCH node may remove the member nodes leaving the community from the corresponding list.

2) The member node loses connection with the CH node. And the CH node does not receive the HB data packet broadcasted by the member node after a period of time, and the updating of the community member table is completed.

Besides updating the table entries maintained by the nodes themselves when receiving the HB or other notification packets of the neighboring nodes, each node in the community also periodically updates the node state thereof to discover the condition that the neighboring nodes lose connection. Meanwhile, the CH node needs to select or update a BCH and GW/BGW list. The time interval between two active node updates is BEAT _ LENGTH. Community COM_kNode ve_iThe contents of the update at time t are as follows:

5) node to ENC value for current community

6) The expected remaining connection time of the neighboring node is reduced by 1. If the value drops to 0, the neighbor node is considered to be no longer connected to the current node.

7) If ve_iAnd if the node is a community CH node, selecting or updating the BCH node at the same time, and informing all nodes in the community of the selected or updated result.

8) And updating the ENC values of the nodes and other communities. If the value changes, the CH node and the BCH node are informed, and the community GW node information is updated.

Wherein, the step 2) is a processing step for ensuring the validity of the neighbor node information. Since the node may disconnect from the neighbor node at any time, the node can only acquire the neighbor node information through the HB data packet periodically broadcast by the neighbor node. Thus, upon receiving the HB packet, the node estimates the connection time ECT with the neighbor node. The ECT is decremented by 1 each time a node actively updates state. When the ECT drops to 0, it indicates that no HB packet was received from the neighbor node for a period of time. At this point, the current node is considered to be no longer connected with the neighbor node.

Description of the attached tables

TABLE 1 simulation experiment parameters for Internet of vehicles with infrastructure

TABLE 2 node ENC value example

Table 3 experimental parameter settings

Drawings

FIG. 1 is a topology diagram of an ad hoc network of the Internet of vehicles

FIG. 2 an example of a gateway node set for an ad hoc network of the Internet of vehicles

FIG. 3 Community node role switching

FIG. 4. tau_i,tCurve of values

FIG. 5 TAPASColone dataset road topology

FIG. 6 distribution of Community population percentage over Community survival time

FIG. 7 distribution of node quantity with node community change times

FIG. 8 distribution of percentage of node number with node packet forwarding

FIG. 9 is a flow chart of the method of the present invention

Detailed Description

The specific implementation process of the invention is shown in fig. 9, and includes the following 5 aspects:

(ii) Community Attribute definition

② definition of community node role

Method for community clustering and role distribution

Experiment of

Analysis of Community stability results

①

Community attribute definition

The invention abstracts the VANET into a structure of a weighted undirected graph. The vehicle nodes serve as points in the undirected graph, and the wireless connections between vehicles serve as edges between the points. The undirected graph with weight is G ═ V_G,E_G). Wherein V_G＝{ve₁,ve₂… represents a set of vertices ve_kRepresenting vertex k. E_G＝{e₁,e₂… represents an edge set, e_jRepresenting edge j. The VANET topology is shown in fig. 1. The community is abstracted into the form of G subgraph, which is recorded as

If two vehicles are within the transmission range of each other, an edge is considered to exist between the nodes abstracted by the two vehicles. Weight w of edge_eIs the vehicle direct connectivity factor (see definition 1). Weight w of a node_veThe expected neighbor is connected to the centrality (see definition 4).

(2) Defining 2 neighbor nodes: if the vehicle A and the vehicle B satisfy TRF(ve_A,ve_B)>0, the A and the B are called as neighbor nodes. Reflected in the topological graph, i.e. ve_AAnd ve_BThere is an edge in between.

In the internet of vehicles, there are many neighbor nodes of some vehicles and many nodes capable of directly communicating. There are few neighbor nodes of some vehicles, and there are few nodes capable of direct communication. The node neighbor connection centrality is defined to represent the number of current neighbor nodes of the vehicle and the closeness of the connection between the vehicle and the neighbor nodes.

Then there are:

where DTS denotes a set of time intervals { dt | dt ═ 0, Δ t,2 Δ t,3 Δ t, … }, and WS denotes a set of weights { w | w ═ w }₁,w₂,…}，w_iRepresenting the weight corresponding to the NCC value at the moment of t + (i-1) delta t. The larger the ENCC value, the more reliable the connection of the vehicle to the surrounding nodes in the future period of time represented by the DTS, and the tighter the connection.

(5) Define 5 Community Neighbor Connection Centrality (CNCC): indicating that the node is at the current timeThe sum of the direct connectivity factors for the nodes within a given community. Let t time ve_iNode pair community COM_kCNCC value of

Then there is

Wherein

Is provided with

Wherein WS and DTS have the meaning as defined in definition 4. The larger the ENC value is, the more the COM value is, the more the_kThe higher the overall quality of the direct connection, the tighter the connection. The influence of the CNCC value at a certain moment can be expanded by adjusting the weight of the CNCC at each time point to focus on considering the CNCC value at the moment.

(7) Define 7 node remaining load capacity (AWL): indicating the buffer space remaining for the node to forward data at the current time. Will ve_iThe AWL value of the node at the time t is recorded as AWL_i,t. At time t, to ve_iNode sending is bigIn AWL_i,tWill cause the packet to be lost.

②

Community node role definition

In addition to the head node and the member nodes, in order to study the connection between the current community and other communities, the concept of a gateway node (GW) is added to the partial community clustering method. The gateway node belongs to one community and is directly connected with nodes of other communities. Generally, the number of gateway nodes in a community and the connection quality of the gateway nodes and other communities can represent the closeness of the community with other communities. In a routing protocol based on community clustering, a gateway node is often used as a relay node for inter-community communication and is responsible for forwarding data packets to other communities.

In the routing protocol based on community clustering, it is because of the special status of the head node and the gateway node, which results in high load of data forwarding. The invention defines a head node waiting node and a gateway node waiting node for balancing loads of the head node and the gateway node, and divides node roles in a community into five classes, namely the head node, the gateway node, the head node waiting node, the gateway node waiting node and a common member node. The role of a node that is not included in the community is defined as a free node.

Then node ve_iIs considered to be in the future for a period of time

where δ is a control factor for the number of BCH nodes selected. At the beginning of community formation, the load of data transmission of the CH node and the BCH node is low, δ can be set to a large value, the number of the BCH nodes is reduced, the connection quality of the selected BCH node in the community is enabled to be closer to the CH node, and therefore the forwarding characteristic of the BCH node is enabled to be closer to the CH node. With the aggravation of the data packet forwarding task in the community, when both the CH node and the selected BCH node reach a very high data load, δ can be appropriately reduced, and more BCH nodes are selected to assist in data forwarding.

namely Community COM_kTo community COM_lGateway node set ofAll nodes of (2) belong to the community COM_kAnd is connected with the community COM_lSome or all of the nodes in (a) are directly connected as shown in fig. 2.

BGWS_k,l＝{ve_i|ve_i≠GW_k,l,ve_i∈GWS_k,l} (11)

And CH_kMust have an edge in between

● for node CM_iThe community of which is COM_kThen equation (12) is satisfied.

Nodes that do not belong to any community are defined as free nodes (SN). The role transitions of the nodes are shown in fig. 3. In one community, the CH node and the BCH node may have the identity of the GW node or the BGW node. In the figure, the arrow direction indicates community node role switching, (B) CH indicates a CH or BCH node, (B) GW indicates a GW or BGW node, and (B) CH (B) GW node indicates a node having both (B) CH role and (B) GW role.

③

Community clustering and role distribution method

The clustering of the communities in the Internet of vehicles is a process of dividing nodes in the Internet of vehicles into different communities. The basis of dividing the nodes is different due to different community clustering algorithms. The invention divides the process of community clustering into two stages of community formation and community maintenance.

(1) Community formation

(2) Community maintenance

After the neighbor node information table is updated, if the node finds that a new CH node appears in the neighbor node, whether the CH node is more suitable to be used as the CH node than the current community CH node is judged. Suppose node ve_iReceive ve_hTransmitted HB packets of which ve_hIs a newly appeared CH node in the neighbor nodes. Here an improvement is made to the testClusterHeadChange algorithm in the MDMAC method. Node ve_hThe following five criteria are satisfied to be considered more suitable for doing ve_iThe head node of (2):

11)ve_hthe node is a CH node of the community in which the node is located;

12) the ENCC value satisfies

13)ve_hAnd ve_iIs sufficiently long;

14)ve_iand ve_hThe included angle of the speed between the two is small enough;

15) suppose ve_iThe community is COM_m，ve_hThe community is COM_nThen the ENC value needs to be satisfied

5) when ve_iWhen not a CH node, ve_iNotification of ve by broadcasting JC packets_hJoin the community. And notify the original community CH node ve_iLeaving the original community, and completing the attribution change of the node community;

6) when ve_iWhen it is a CH node, ve_iNotification of ve by broadcasting JC packets_hJoin the community. And other nodes in the community are informed, and the original community disappears. Other node changes within a communityIs an SN node. And then according to the received HB data packets of other CH nodes, selecting to join other communities to complete the combination of the communities. Or self-electing to be a new community CH node, attracting surrounding nodes to join, and completing the division of the community.

(b) BCH, GW and BGW node role allocation

To COM_jMaximum ve of community ENC₃The node is selected as the community COM_iTo community COM_jGW node of (1), the remaining 4 nodes being selected as community COM_iTo community COM_jThe BGW node of (1). The GW and BGW nodes are only at C, because the gateway node tables of the community are maintained only at CH and BCH nodesH and BCH nodes. In the self-election process of the gateway node, the nodes all consider themselves to be the BGW nodes.

9) node to ENC value for current community

10) The expected remaining connection time of the neighboring node is reduced by 1. If the value drops to 0, the neighbor node is considered to be no longer connected to the current node.

11) If ve_iIs a CH node of the community, thenAnd selecting or updating BCH nodes at the same time, and informing all nodes in the community of the selected or updated result.

12) And updating the ENC values of the nodes and other communities. If the value changes, the CH node and the BCH node are informed, and the community GW node information is updated.

Experiment of

(1) Experimental data set

The simulation experiment of the invention adopts a vehicle networking simulation framework of Venns, and the data set is TAPASColone. The TAPASColone dataset is derived from the Institute of Transportation Systems at the German Aerospace Center (ITS-DLR), and contains a road topology network of a real German city, Koron. The moving track of the microscopic vehicle nodes in the urban road can be simulated by SUMO traffic simulation software to describe the traffic flow of 24 hours in the 400 square kilometer area of the German Kolon city. The data set road topology is shown in fig. 5.

According to the invention, vehicle track data in a time period of 6: 00-8: 00(am) is adopted in an experiment to provide a vehicle node movement basis for vehicle networking simulation. In the time period, at most more than 8000 vehicle nodes can run on the road simultaneously, and the requirement of the experiment of the invention on vehicle track simulation can be met.

(2) Experimental methods

And respectively using an MDMAC method and the PMRC method to perform community clustering on vehicles in a period of 6: 00-8: 00(am) in the TAPASColone data set and dynamically updating the community form of the vehicles. And (4) counting the survival time of the VANET community formed under the two methods and the number of times of change of the node community in the community. The statistical results were compared to compare the stability of the communities formed by the PMRC and MDMAC methods. After the community is formed, a source node and a destination node for sending data packets are selected according to the same random mode, the data packets are sent periodically, and the number of data packets forwarded by each node in the community, the delivery rate of the data packets and the average end-to-end delay are recorded. And comparing the statistical results to compare the performances of the VANET community obtained by the two methods in the community routing of the Internet of vehicles. Wherein the packet delivery rate represents the ratio of the number of packets successfully arriving at the destination node to the total number of packets to be transmitted. The average end-to-end delay represents the average length of time required for a data packet to be sent by a source node to a destination node.

The selection rule of the data forwarding node is as follows:

1) if the destination node is a direct neighbor node of the current data packet holding node, directly forwarding the data packet to the destination node;

2) if the current data packet holding node is a CM node, selecting a node from the head node pool as a next hop for forwarding the data packet;

3) if the current data packet holding node is a CH node or a BCH node, whether a destination node is a node of the community is judged firstly. If so, the data packet is directly sent to the destination node. Otherwise, selecting a proper community from the neighbor communities to forward the data packet, and selecting a node from the gateway node pool as a next hop for forwarding the data packet;

4) if the current data packet holding node is a GW node or a BGW node, selecting a next forwarding community node in a neighbor node table as a next hop of data packet forwarding according to the next forwarding community information marked by the data packet;

5) if the 4 conditions are not met, the node continues to hold the data packet and waits for the four sending conditions to be met.

In the formula (15), ρ is 1 and μ is 20 KB. The remaining experimental parameter settings are shown in table 3.

Community stability result analysis

FIG. 6 shows the community proportion of different community survival time periods obtained by the PMRC method and the MDMAC method. From left to right in the figure, the community survival time intervals (0,20s ], (20s,40s ], …, (480s,500s ]) are respectively shown, and the community proportion is rapidly reduced along with the increase of the community survival time due to the fast moving speed of the vehicle nodes in the figure, in the MDMAC community clustering, the community survival time is less than 66.76% of all communities of 20s, the community survival time obtained by the PMRC method clustering is less than 51.77% of all communities of 20s, in the MDMAC method, the average survival time of the communities is 42.91 seconds, the average survival time obtained by the PMRC method clustering is 75.95 seconds, therefore, the PMRC method clustering has longer survival time than the communities obtained by the MDMAC method clustering.

The number of node community changes refers to the number of times the node experiences joining a new community. FIG. 7 shows the distribution of the number of nodes with the number of changes to the community of nodes. It can be seen from the figure that, as the number of times of change of the node community increases, the number of nodes corresponding to the statistical result obtained by the MDMAC and PMRC methods increases rapidly and then decreases gradually. In the MDMAC method, the number of nodes that undergo 7 community changes is the largest. The number of nodes that undergo 6 community changes in the PMRC method is the largest. The number of nodes which undergo community change for less than 8 times by the PMRC method is greater than that by the MDMAC method. The MDMAC method is more than the PMRC method in the number of nodes that undergo more than 8 community changes. The average community change frequency experienced by the nodes in the MDMAC method is 9.04 times, and the average community change frequency experienced by the nodes in the PMRC method is 8.45 times. Therefore, the number of community changes experienced by nodes in the PMRC method is generally less than the MDMAC method. In conclusion, the stability of the internet of vehicles community formed by the PMRC method is superior to that of the MDMA method.

The innovation points are as follows: based on a vehicle position prediction model (inventor of Chengdu et al, applied in 2017, 8, 16, and applied in 'a position prediction model construction method for vehicle driving influence factors based on deep learning in a vehicle networking complex network' (applicant: university, patent application No. 2017107029220), a multi-role classification community clustering method under a vehicle networking self-organization network scene is provided, so that community stability is improved, and data transmission distortion is reduced.

Attached table of the specification

TABLE 1

TABLE 2

Node point	ve₁	ve₂	ve₃	ve₄	ve₅
						ENC	3.516	2.871	6.220	1.155	5.031

TABLE 3

Claims

1. A head node screening method of a self-organizing network of the Internet of vehicles is characterized by comprising two parts,

community attribute and community node role definition of Internet of vehicles self-organizing network

Step 1.1, the community attributes are defined as follows:

abstracting VANET into a structure with a weight undirected graph; the vehicle nodes are taken as points in the undirected graph, and the wireless connection between the vehicles is taken as an edge between the points; the undirected graph with weight is G ═ V_G，E_G) (ii) a Wherein V_G＝{ve₁，ve₂，...ve_kDenotes the set of vertices, ve_kRepresents vertex k; e_G＝{e₁，e₂，...e_jDenotes an edge set, e_jRepresents edge j; the communities are represented by vertex sets and edge sets, and are abstracted into a G subgraph form and are marked as

If two vehicles are in the transmission range of each other, an edge is considered to exist between the abstract nodes of the two vehicles;

(1) definition 1 vehicle direct connectivity factor TRF: representing the reliability of the connection between two vehicle nodes, and satisfying the formula (2);

wherein TR represents a maximum transmission range of vehicle communication; dist_t(ve_i，ve_j) Represents the distance between the vehicle i and the vehicle j at the moment t; when the distance between the vehicles is greater than the maximum transmission range, the TRF is 0, and the two vehicle nodes are not connected; reflected on the topological graph, namely that no edge exists between the two nodes; when the distance between the vehicles is less than or equal to the maximum transmission range, the TRF is inversely related to the distance between the vehicles; the closer the distance is, the larger the TRF is, the higher the reliability of the connection between two vehicle nodes is, the closer the connection is, and the greater the weight reflected to the upper side of the topological graph is;

(2) defining 2 neighbor nodes: if the vehicle A and the vehicle B satisfy TRF (ve)_A，ve_B) If the number is more than 0, the A and the B are called as neighbor nodes; reflected in the topological graph, i.e. ve_AAnd ve_BAn edge is arranged between the two edges;

the node neighbor connection centrality is defined to represent the number of the current neighbor nodes of the vehicle and the contact tightness between the vehicle and the neighbor nodes;

(3) defining 3 neighbor connection centrality NCC: representing the sum of direct connectivity factors of the node and the neighbor nodes;

will ve_iThe NCC value of the node at the time t is recorded as C_i，tThen, there are:

wherein the NS_iA set of neighbor nodes representing inodes; the larger the NCC is, the higher the reliability degree of the connection between the node and the nodes around the node is, and the closer the connection is;

(4) defining 4 expected neighbor connection centrality ENCC: representing a weighted average of the NCC values of the nodes for a future period of time from the current time; node ve at time t_iHas an ENCC value of

Then there are:

where DTS denotes a set of time intervals { dt | dt ═ 0, Δ t,2 Δ t,3 Δ t₁，w₂，...}，w_kRepresenting the weight corresponding to the NCC value at the t + (i-1) delta t moment; the larger the ENCC value is, the higher the connection reliability of the vehicle and the surrounding nodes in the future period of time represented by the DTS is, and the closer the connection is;

(5) defining 5 community neighbor connection centrality CNCC: indicates that the node is atThe sum of direct communication factors of nodes in the designated community at the previous moment; let t time ve_iNode pair community COM_kCNCC value of

Then there is

Wherein

Is denoted ve_iCOM (component object model) of node-in-community_kA set of neighboring nodes; the CNCC represents the direct connection quality of the vehicle node and a certain community as a whole; the bigger the CNCC value is, the more the COM value is, the more the node is currently connected with the community_kThe higher the overall direct connection quality, the tighter the connection;

(6) defining 6 expected community neighbor connection centrality ENC: representing the weighted average of the CNCC values of the designated community by the nodes at a period of time after the current moment; let t time ve_iNode pair community COM_kThe ENC value of (A) is recorded as

Is provided with

The larger the ENC value is, the more the COM value is, the COM value is with the community in the future_kThe higher the overall direct connection quality, the tighter the connection;

(7) defining 7 nodes residual load capacity AWL: representing the buffer space left by the node at the current moment for forwarding data; will ve_iThe AWL value of the node at the time t is recorded as AWL_i，t(ii) a At time t, to ve_iNode transmission greater than AWL_i，tWill cause the packet to be lost;

step 1.2 community node role definition of the vehicle networking self-organizing network

Balancing loads of a head node and a gateway node, defining a head node waiting node and a gateway node waiting node, and dividing node roles in a community into five classes, namely the head node, the gateway node, the head node waiting node, the gateway node waiting node and a common member node; defining the role of the node which is not included in the community as a free node;

(1) define 8 head node CH: the node with the highest ENC value in the community; is provided with

Then node ve_iIs considered to be in the future for a period of time

The connection quality in the community is the best; the node is selected as COM_kA CH node of (2); if a plurality of nodes with the highest ENC values exist, selecting the node with the lowest number as a CH node;

(2) defining 9 head node waiting nodes BCH: the nodes with high adjacent centrality of the expected community in the community; for community COM_kIn other words, the CH node is ve_hThen, the BCH node of the community needs to satisfy:

h represents the number of the CH node; wherein, delta is a control factor of the number of the head node waiting nodes; at the beginning of community formation, the load of data transmission of the head node and the head node waiting node is low; with the aggravation of a data packet forwarding task in a community, a head node waiting node is added to assist data forwarding;

(3) defining 10 Community COM_kTo community COM_lThe gateway node set GWS: defined as set GWS_k，lAnd satisfies the following conditions:

namely Community COM_kTo community COM_lAll nodes of the gateway node set belong to the community COM_kAnd is connected with the community COM_lSome or all of the nodes in the network are directly connected;

(4) defining 11 Community COM_kTo community COM_lGateway node GW of_k，l: defined as set GWS_k，lMiddle-to-community COM_lNode with the largest ENC value; i.e. if ve_i∈GWS_k，lThen, it needs to satisfy:

if GWS is_k，lCOM in community_lIf the number of the nodes with the maximum number of the ENCs is multiple, the node with the lowest number is selected as the community COM_kTo community COM_lA gateway node (GW);

(5) defining 12 Community COM_kTo community COM_lGateway node waiting node set BGWS_k，l: is defined as GWS_k，lRemoving gateway node GW_k，lAll nodes other than that, i.e.

BGWS_k，l＝{ve_i|ve_i≠GW_k，l，ve_i∈GWS_k，l} (11)

BGWS_k，lThe node in (1) is defined as a community COM_kTo community COM_lGateway node waiting node BGW_k，l；

Common member nodes (CM) refer to CH nodes, BCH nodes, GW nodes and all other community nodes except BGW nodes in the community; the CM node conforms to the following two characteristics:

CM nodes are single hop neighbor nodes of community CH nodes; namely for community COM_kThe CH node is CH_kThen CM node

And CH_kThere must be an edge e between_j，

For node CM_iThe community of which is COM_kThen equation (12) is satisfied;

defining nodes which do not belong to any community as free nodes SN;

community clustering and role distribution method for Internet of vehicles self-organizing network

The vehicle networking community clustering is a process of dividing nodes in the vehicle networking into different communities;

in the initialization stage of the self-organizing network of the Internet of vehicles, each vehicle node is initialized to be an SN node; then, no matter in a community forming stage or a community maintenance stage, the node always broadcasts heartbeat control (HB) data packets to the neighbor nodes periodically; the HB data packet carries node state information, including the current position of the node, the future positions of 1s, 2s and 3s obtained by the node through prediction based on a vehicle position prediction model, the community to which the node belongs, the node ENCC value, the node ENC value, the node AWL value and the like; all nodes maintain a neighbor information table neighbor Table for calculating and comparing ENCC index data and ENC index data of neighbor nodes, wherein BEAT _ LENGTH represents the time interval of sending two adjacent HB data packets; the neighbor node and ve are considered as if the HB data packet of longer time is missing_iThe node is disconnected, and the information of the node is removed from the neighbor information table;

the node ve_hIf the following five criteria are satisfied, then it is considered as ve_iThe head node of (2):

1)ve_hthe node is a CH node of the community in which the node is located;

2) the ENCC value satisfies

3)ve_hAnd ve_iThere is an expected connection time;

4)ve_iand ve_hA velocity angle exists;

5) suppose ve_iThe community is COM_m，ve_hThe community is COM_nThen the ENC value needs to be satisfied

Meeting these criteria guarantees ve_hThe nodes have better direct connectivity, and ve is ensured_iNode and ve_hThe communities in which the nodes are located are more closely related; at the same time ensure ve_hAnd ve_iHave a longer time connection between them, can avoid ve_iFrequently joining and leaving communities;

if ve_hMore suitable as CH node, then ve_iSelectively add ve_hThe community in which the user is located; ve_iThe following operations are carried out according to the role of the user:

1) when ve_iWhen not a CH node, ve_iNotification ve by broadcasting community request data packet JC_hJoining the community; and notify the original community CH node ve_iLeaving the original community, and completing the attribution change of the node community;

2) when ve_iWhen it is a CH node, ve_iNotification ve by broadcasting community request data packet JC_hJoining the community; other nodes in the community are informed, and the original community disappears; other nodes in the community become SN nodes; then according to the received HB data packets of other CH nodes, other communities are selected to be added, and the combination of the communities is completed; or self-electing to be a CH node of a new community, attracting surrounding nodes to join, and completing the splitting of the community;

2. The method for screening the head nodes of the self-organizing network of the internet of vehicles according to claim 1, wherein the process of community clustering is divided into two stages of community formation and community maintenance:

step 2.1 Community formation

Community formation begins with election of a community CH node; when the node updates the self ENCC value, the self ENCC value is compared with the ENCC value of the neighbor node, so that the node with the maximum ENCC value is found; the node with the largest ENCC value is suitable to be selected as the CH node; when a plurality of nodes with the maximum ENCC value exist, selecting the node with the minimum ID value as a CH node; after the CH node is selected, the ID of the new community is marked as the ID of the CH node, and the neighbor node learns the establishment of the new community through an HB data packet broadcasted by the CH node; if the neighbor node is the SN node, directly joining the community, and informing the CH node in the form of a joining community request data packet JC; if the neighbor node belongs to other nodes, judging whether the neighbor node is suitable for being added into a new community, and detailing the judgment according to the judgment in a community maintenance stage; the CH node updates a community member table according to the received JC data packet; if the JC data packet represents the request to join the community, adding a JC data packet sending node into a community member table; if the JC data packet requests to join other communities, the node sending the data packet is moved out of a community member table; after a plurality of iterations, the community gradually tends to a stable state; at this time, the process of community formation is completed;

step 2.2 Community maintenance

In the community maintenance stage, the conditions of dynamic addition or departure of nodes in a community and combination, splitting and extinction of the community need to be processed; meanwhile, the role distribution of BCH, GW and BGW nodes is also carried out in the community maintenance phase;

At this stage, the problem of node community attribution change needs to be handled; when a node receives an HB data packet broadcasted by a neighbor node, predicting the connection duration of the node and the neighbor node according to the speed, the current position and the predicted positions at the future time of 1s, 2s and 3s, and updating a neighbor node information table;

after updating the neighbor node information table, if the node finds that a new CH node appears in the neighbor node, judging whether the CH node is more suitable to be used as a CH node than the current community CH node; node ve_iReceive ve_hTransmitted HB packets of which ve_hIs a newly appeared CH node in the neighbor nodes;

(b) BCH, GW and BGW node role allocation

In the community maintenance phase, the problem of role allocation of BCH, GW and BGW nodes also needs to be solved; the CH and the BCH node maintain the same community member list; the CH and BCH nodes respectively maintain a gateway information table according to the updated information of the GW and the BGW nodes in the neighbor nodes; the CH node maintains a community member list and knows the community status of each node in the community; the common nodes of the community do not store a community member list, and the status of each node in the community cannot be known; therefore, in order to select a node having a similar community status as the CH node as a BCH node, the BCH node is designated by the CH node; other nodes in the community can know the adjacent community and can calculate the ENC value of the adjacent community; therefore, GW and BGW nodes are self-elected by each node in the community and announce the result to CH node and adjacent BCH node;

the BCH node is selected to be a node which is closer to the ENC value of the CH node according to the size of the ENC value and is more suitable to be used as the BCH node;

selecting the GW and the BGW nodes according to the ENC value of the adjacent community; suppose COM_iThere are 5 nodes and COM in the community_jNodes in the community are directly connected; the 5 nodes are represented as<ve₁，ve₂，ve₃，ve₄，ve₅>；

To COM_jMaximum ve of community ENC₃The node is selected as the community COM_iTo community COM_jGW node of (1), the remaining 4 nodes being selected as community COM_iTo community COM_jThe BGW node of (1); since only the gateway node tables of the community are maintained at the CH and BCH nodes,the GW and BGW nodes are only distinguished at the CH and BCH nodes; in the self-election process of the gateway node, the nodes all consider to be BGW nodes;

the CH node and the BCH node need to maintain community member lists, wherein the community member lists comprise a CH node list, a BCH list, a GW/BGW list and a CM list; the CH node list, the BCH list and the GW/BGW list are collectively called a key node member list; in the process of election of BCH and GW/BGW, the CH node and the corresponding BCH node update the member list of the key nodes according to the election result; after the CM node joins the community, the CH node and the corresponding BCH node update the CM list; when the member node in the community leaves the community, the CH node and the BCH node remove corresponding members, and corresponding new role selection is performed according to the roles of the removed members; the member nodes leave the community can be divided into the following two cases:

1) the member node joins in other communities and actively informs the CH node and the corresponding BCH node; at this time, the CH node and the BCH node remove the member nodes leaving the community from the corresponding list;

2) the member node loses connection with the CH node; the CH node does not receive the HB data packet broadcasted by the member node after a period of time, and the updating of the community member table is completed;

besides updating the table entries maintained by the nodes when receiving HB (hybrid automatic repeat) or other notification data packets of the neighbor nodes, each node in the community can also periodically update the node state of the node so as to discover the condition that the neighbor nodes lose connection; meanwhile, the CH node needs to select or update a BCH and GW/BGW list; the time interval between two times of node active updating is BEAT _ LENGTH; community COM_kNode ve_iThe contents of the update at time t are as follows:

1) node to ENC value for current community

2) Subtracting 1 from the expected residual connection time of the neighbor node; if the value is reduced to 0, the neighbor node and the current node are considered not to be connected any more;

3) if ve_iFor the CH node of the community, the same appliesSelecting or updating BCH nodes, and informing all nodes in the community of the selected or updated result;

4) updating the ENC values of the nodes and other communities; if the value changes, the CH node and the BCH node are informed, and the community GW node information is updated.

3. The method for screening the head nodes of the ad hoc network in the vehicle networking according to claim 1, wherein the step 2) is a processing step for ensuring the validity of the information of the neighbor nodes; because the node may be disconnected with the neighbor node at any time, the node can only acquire the neighbor node information through the HB data packets periodically broadcast by the neighbor node; therefore, when receiving the HB data packet, the node estimates the connection time ECT with the neighbor node; subtracting 1 from ECT every time the node actively updates the state; when the ECT is reduced to 0, the HB data packets from the neighbor nodes are not received for a period of time; at this point, the current node is considered to be no longer connected with the neighbor node.