WO2020215530A1 - Node performance-based opportunity forwarding method in internet of vehicles - Google Patents

Node performance-based opportunity forwarding method in internet of vehicles Download PDF

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WO2020215530A1
WO2020215530A1 PCT/CN2019/099807 CN2019099807W WO2020215530A1 WO 2020215530 A1 WO2020215530 A1 WO 2020215530A1 CN 2019099807 W CN2019099807 W CN 2019099807W WO 2020215530 A1 WO2020215530 A1 WO 2020215530A1
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node
candidate
message
encounter
nodes
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PCT/CN2019/099807
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French (fr)
Chinese (zh)
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朱依水
杨阳
唐蕾
樊娜
陈柘
武博
严昱文
段宗涛
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长安大学
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/18—Communication route or path selection, e.g. power-based or shortest path routing based on predicted events
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Definitions

  • the invention belongs to the field of wireless communication, and particularly relates to an opportunity forwarding method based on node efficiency in the Internet of Vehicles.
  • VANETs Vehicular Ad-hoc Networks
  • MANET Mobile Ad-hoc Networks
  • DSRC Dedicated Short Range Communication
  • VANETs Vehicle-to-everything networks
  • ITS Intelligent Transportation Systems
  • the network aims to exchange relevant traffic service information to improve the safety and efficiency of the road traffic system, and ultimately realize the deep integration of people, vehicles, roads, and the environment, and improve the efficiency of traffic travel.
  • VANETs rely on wireless short-range communication technology to achieve a variety of communication modes, including: (1) Vehicle-to-Vehicle Communication (V2V); (2) Vehicle-to-RSU Communication, V2R) communication; (3) Roadside unit and roadside unit (RSU-to-RSU Communication, R2R) communication; (4) V2X communication, that is, hybrid mode, due to the complexity of the traffic environment, for better This hybrid mode is generally adopted to realize the sharing of data service information locally. Because the topological structure of VANETs is closely related to road layout, vehicle node movement, communication environment and other factors, the specific features are: 1) The complexity of the communication traffic environment: the change of vehicle node direction, the uneven vehicle density, the influence of buildings, etc. More sophisticated methods of information dissemination are needed.
  • the network topology is highly dynamic and non-uniform: Due to the fast moving speed of vehicles and the extremely uneven distribution of vehicle density on the road, the network topology is constantly changing.
  • the predictability of node movement The movement of vehicle nodes is limited by factors such as road structure, traffic laws, vehicle density, traffic conditions, and road speed limits. Comprehensively consider these factors and according to the traveler's social characteristics and historical trajectory information, construct a movement trajectory prediction model.
  • Strong traffic information acquisition and processing capabilities The development of vehicle-mounted sensor equipment provides support for vehicle-mounted self-organizing network routing to obtain traffic information, including positioning data provided by GPS navigation system, speed and direction information provided by vehicle speed detectors Both can be used as an important basis for routing decisions.
  • Routing protocol based on geographic location information The location of the vehicle node itself, neighbors and destination can be obtained through GPS equipment. Judge the route selected by the next hop.
  • Routing algorithm based on movement trajectory information mining the historical driving trajectory of the vehicle or global satellite navigation (GPS) system, combining the current driving path, position, speed, direction and other information of the vehicle can predict the future driving path of the vehicle.
  • Opportunistic routing algorithm based on flooding control Increase the number of copies of the same data packet by copying, and use the flooding mechanism to deliver the copy of the data packet message to as many nodes as possible.
  • Opportunistic forwarding algorithm based on historical information Count the historical information of vehicle nodes and the evaluation of the probability of successful delivery of data packets in the historical process, and purposefully forward data packets to neighboring nodes.
  • the traditional routing algorithm does not consider the effectiveness of the forwarding node, and ignores the transfer potential of the relay node, transmission reliability, and the node’s own resource utilization, which leads to the node The difference. Blindly and equally distribute the number of message copies.
  • This algorithm has low message forwarding efficiency in a network that can be divided into areas.
  • the purpose of the present invention is to provide an opportunity forwarding method based on node efficiency in the Internet of Vehicles, and solve the technical problem of low message forwarding efficiency in the prior art.
  • Step 2 the candidate node i N i copies of the received messages forwarded to the destination node d, comprising the steps of:
  • Step 2.1 Use candidate node i as the current node to be forwarded
  • Step 2.2 take the first node encountered by the current node to be forwarded as the current relay node. If the angle between the movement direction of the current relay node and the movement direction of the destination node d is less than 90°, go to step 2.4; otherwise, Perform step 2.3;
  • Step 2.3 if the encounter index of the current relay node is greater than the encounter index of the current node to be forwarded, perform step 2.4;
  • Step 2.4 the current node to be forwarded to forward a copy of the message to the N i th relay node of the current;
  • Step 2.5 the current relay node as a current node to be forwarded, step 2.2 through step 2.4 is repeated until the N i th forward a copy of the message to the destination node d.
  • step of requesting a vehicle assigned to the candidate node s to node i N i copies of messages comprising the steps of:
  • Step 1.1 calculate the transmission message utility value U i of candidate node i by formula 1:
  • ⁇ represents adjustable parameters, ⁇ (0,1);
  • P(i,d) represents the predicted value of the probability of encounter between the candidate node i and the destination node d
  • P(j,d) represents the predicted value of the probability of encounter between the candidate node j and the destination node d
  • Step 1.2 The transmission of the message utility value of the U-candidate node i, i, s allocated node to a vehicle number of message copies candidate node N i i obtained by requesting formula 2:
  • U s represents the utility value of the transmission message of the requested vehicle node s.
  • P(i,d) old is the last updated encounter probability value of the candidate forwarding node r and the destination node d;
  • k is the influence factor on the forwarding probability during the encounter duration, k>1;
  • P init is the initial constant, 0 ⁇ P init ⁇ 1;
  • ⁇ is the influencing factor of the duration of encounter between nodes, Is the total length of time the candidate node i and the destination node d meet q times; Is the total time of the encounter between the candidate node i and other nodes in the Internet of Vehicles except the destination node d; It is the total duration of the encounter between the destination node d and other nodes in the Internet of Vehicles except the destination node d.
  • Hops (i, d) represents the number of hops experienced by the current relay node i to the destination node d; Indicates the number of nodes contacted by the current relay node in the past unit time T; Represents the average number of nodes that the current relay node has contacted in the past unit time T.
  • the present invention has the following beneficial technical effects:
  • the present invention selects a suitable relay node for forwarding through the multi-hop information carried between nodes and the statistical information of the historical movement process, so as to quickly realize data transmission and information sharing between mobile vehicle nodes.
  • the present invention dynamically allocates the number of message copies based on the transmission efficiency of the node, which not only can better improve the successful transmission efficiency of the message, but also can avoid the waste of network resources caused by the transmission of messages by nodes with weaker transmission capabilities.
  • the present invention introduces the probability prediction information of the vehicle node, the geographic location information, the movement attribute of the node and the encounter index as the judgment basis, and selects a more suitable relay node to improve the message transmission rate in the Internet of Vehicles and reduce the message transmission delay
  • the overall performance of the network link such as network load and average number of hops.
  • Figure 1 is a time process diagram of encounter and connection between nodes
  • Figure 2 is a flow chart of data forwarding in the Spray phase
  • Figure 3 is a schematic diagram of the prediction value comparison process
  • FIG. 4 is a flowchart of data forwarding in the Wait phase
  • Figure 5 is a schematic diagram of a node motion scene
  • Figure 6 is a schematic diagram of the movement direction of the node.
  • This embodiment provides an opportunity forwarding method based on node efficiency in the Internet of Vehicles.
  • the vehicle node s is requested to generate a message and needs to forward the message to the destination node d.
  • the requesting vehicle node s can be any vehicle in the Internet of Vehicles. Node, including the following steps:
  • the Internet of Vehicles in the present invention may be an Internet of Vehicles network of urban road traffic, in which all nodes are vehicles in the Internet of Vehicles network.
  • Step 1.1 calculate the transmission message utility value U i of candidate node i by formula 1:
  • ⁇ represents an adjustable parameter, which is used to adjust the relative importance of two utility values, ⁇ (0,1);
  • P(i,d) represents the predicted value of the probability of encounter between the candidate node i and the destination node d
  • P(j,d) represents the predicted value of the probability of encounter between the candidate node j and the destination node d
  • P(i,d) old is the last updated encounter probability value of the candidate forwarding node r and the destination node d;
  • k is the influence factor on the forwarding probability during the encounter duration, k>1;
  • P init is the initial constant, 0 ⁇ P init ⁇ 1;
  • ⁇ is the influencing factor of the duration of encounter between nodes, Is the total length of time the candidate node i and the destination node d meet q times; Is the total time of the encounter between the candidate node i and other nodes in the Internet of Vehicles except the destination node d; It is the total duration of the encounter between the destination node d and other nodes in the Internet of Vehicles except the destination node d.
  • Figure 1 illustrates that the encounter duration represents the time that the communication link established by two nodes can maintain a continuous connection state. This setting is the minimum encounter connection time that allows two nodes to send data packets to each other, thereby preventing two nodes from not having enough time In the case of communication time, start sending data packets to other vehicle nodes.
  • Step 1.2 The transmission of the message utility value of the U-candidate node i, i, s allocated node to a vehicle number of message copies candidate node N i i obtained by requesting formula 2:
  • U s represents the utility value of the transmission message of the requested vehicle node s.
  • the present invention takes into account the mobility of the nodes in the Internet of Vehicles environment, and the differences in the transfer potential of the relay node, the transmission reliability, the node's own resource utilization, etc. cause the differences of the nodes. Because the Spray phase of the Spray and Wait routing mechanism ignores factors such as the different ability of each node to transmit messages, the intricate network topology, and the historical encounter information of the nodes, the transmission process is blind and not flexible enough. Therefore, comprehensively consider the predicted utility value of the vehicle node based on the probability of the encounter connection time and the statistical utility value of the connection of the node in the historical process, jointly evaluate the message transmission capacity of the node, and treat different nodes differently, so that the distribution of message copies More reasonable and efficient. Send the message as far as possible to the next hop node that can establish a reliable connection with its own node and maintain a good communication link, thereby enhancing the effectiveness of message transmission.
  • the present invention proposes a mechanism for dynamically allocating the number of message copies according to the different transmission capabilities of nodes.
  • the Spray phase of the Spray and Wait routing mechanism because it distributes message copies to the meeting nodes in a fixed and equal manner, this process fails to take into account The difference of meeting nodes. Therefore, a calculation model of node transmission capacity is introduced, and the number of message copies is dynamically allocated through the node performance value calculated by the model. Specifically, the greater the relay node's ability to deliver messages, the more message copies should be allocated to the node, which changes the original traditional Spray and Wait routing algorithm's blind and equal distribution mechanism in the Spray phase.
  • the present invention fully considers the reliability and effectiveness of link transmission, makes the forwarding decision in the process more reasonable and efficient, and completes the transmission of the message copy at a faster speed.
  • the dissemination mechanism of this method enables mobile vehicle nodes to better adapt to the constantly changing network environment.
  • Step 2 the candidate node i N i copies of the received messages forwarded to the destination node d, as shown in FIG 4, comprising the steps of:
  • Step 2.1 Use candidate node i as the current node to be forwarded
  • Step 2.2 take the first node encountered by the current node to be forwarded as the current relay node. If the angle between the movement direction of the current relay node and the movement direction of the destination node d is less than 90°, go to step 2.4; otherwise, Perform step 2.3;
  • the movement direction in this embodiment may also be movement attributes such as movement speed.
  • Step 2.3 if the encounter index of the current relay node is greater than the encounter index of the current node to be forwarded, proceed to step 2.4; if the current relay node encountered by the current node to be forwarded does not meet the above two conditions, then the current node to be forwarded The carried copy of the message fails to be forwarded.
  • Hops (i, d) represents the number of hops experienced by the current relay node i to the destination node d; Indicates the number of nodes contacted by the current relay node in the past unit time T; Represents the average number of nodes that the current relay node has contacted in the past unit time T, and T represents the update time of the node encounter index.
  • Step 2.4 the current node to be forwarded to forward a copy of the message to the N i th relay node of the current;
  • Step 2.5 the current relay node as a current node to be forwarded, step 2.2 through step 2.4 is repeated until the N i th forward a copy of the message to the destination node d.
  • the present invention establishes a message transmission selection model based on the node motion attributes and the encounter index of the vehicle node, so that the original way of passively waiting for the destination node becomes actively looking for the next hop node, that is, when the current node has a neighbor node in its communication range, Choose a more efficient relay node to transmit the message to the destination faster.
  • the motion attributes of moving vehicles are very important in the data forwarding decision. Therefore, using the motion characteristics of vehicle nodes in the Internet of Vehicles can effectively improve the transmission efficiency of data packets and reduce message forwarding delay.
  • the node encounter index is used as a supplement to the node's motion attributes. If the node's motion attributes do not meet the requirements, the node encounter index is judged to increase the choice dimension of the relay node.
  • the data forwarding model in the Wait phase is shown in Figure 5.

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Abstract

The present invention provides a node performance-based opportunity forwarding method in Internet of vehicles, comprising the following steps: step 1, a request vehicle node s generates a message and needs to forward the message to a destination node d; the number of message copies carried by the message requiring forwarding is N, and the request vehicle node s allocates Ni message copies to candidate nodes i, wherein i=1, 2,..., n, Ni≤N, and the candidate nodes are all nodes within a communication range of the request vehicle node s; step 2, the candidate nodes i forward the received Ni message copies to the destination node d. The present invention makes an improvement to the existing Spray and Wait routing mechanism, thereby improving message forwarding efficiency.

Description

一种车联网中基于节点效能的机会转发方法Opportunity forwarding method based on node efficiency in car network 技术领域Technical field
本发明属于无线通信领域，具体涉及一种车联网中基于节点效能的机会转发方法。The invention belongs to the field of wireless communication, and particularly relates to an opportunity forwarding method based on node efficiency in the Internet of Vehicles.
背景技术Background technique
车联网(Vehicular Ad-hoc Networks,VANETs)是由移动自组织网络(MANET)发展而来，可以在没有基础设施的情况下自主组织网络，并且以车辆作为网络节点，集成了Ad hoc网络，无线和蜂窝通信技术的功能，其中DSRC(专用短程通信)的标准化使得车辆和路侧单元能够形成VANETs，是智能交通***(ITS)的核心组成部分。该网络旨在交换相关交通服务信息，以提高道路交通***的安全性和高效性，最终实现人、车、路、环境深度融合，提高交通出行效率。VANETs依靠无线短距离通信技术实现了多种通信模式，其中：(1)车与车通信(Vehicle-to-Vehicle Communication,V2V)；(2)车与路边单元(Vehicle-to-RSU Communication,V2R)之间的通信；(3)路边单元与路边单元(RSU-to-RSU Communication,R2R)的通信；(4)V2X通信，即混合模式，由于交通环境的复杂性，为了更好地实现交数据服务信息共享，一般采用该混合模式。由于VANETs的拓扑结构与道路布局、车辆节点运动、通信环境等因素密切相关，因此具体特征有：1)通信交通环境的复杂性：车辆节点方向的变化、车辆密度不均匀、建筑物等的影响需要更复杂的信息传播方式。2)网络拓扑具有高动态性与非均匀性：由于车辆移动速度较快、道路上车辆密度分布极不均匀，导致网络拓扑不断变化。3)节点的移动可预测性：车辆节点的移动受限于道路结构、交通法规、车辆密度、车流 状况以及路段限速等因素的影响。综合考虑这些因素以及根据出行者的社会特征和历史轨迹信息，构建移动轨迹预测模型。4)交通信息的获取与处理能力较强：车载传感器设备的发展对于车载自组织网络路由获取交通信息提供了支持，其中GPS导航***提供的定位数据、车辆速度检测仪提供的速度及方向等信息都可作为路由决策的重要依据。Vehicular Ad-hoc Networks (VANETs) are developed from Mobile Ad-hoc Networks (MANET), which can organize networks autonomously without infrastructure, and use vehicles as network nodes to integrate Ad hoc networks, wireless And the functions of cellular communication technology, in which the standardization of DSRC (Dedicated Short Range Communication) enables vehicles and roadside units to form VANETs, which are the core components of Intelligent Transportation Systems (ITS). The network aims to exchange relevant traffic service information to improve the safety and efficiency of the road traffic system, and ultimately realize the deep integration of people, vehicles, roads, and the environment, and improve the efficiency of traffic travel. VANETs rely on wireless short-range communication technology to achieve a variety of communication modes, including: (1) Vehicle-to-Vehicle Communication (V2V); (2) Vehicle-to-RSU Communication, V2R) communication; (3) Roadside unit and roadside unit (RSU-to-RSU Communication, R2R) communication; (4) V2X communication, that is, hybrid mode, due to the complexity of the traffic environment, for better This hybrid mode is generally adopted to realize the sharing of data service information locally. Because the topological structure of VANETs is closely related to road layout, vehicle node movement, communication environment and other factors, the specific features are: 1) The complexity of the communication traffic environment: the change of vehicle node direction, the uneven vehicle density, the influence of buildings, etc. More sophisticated methods of information dissemination are needed. 2) The network topology is highly dynamic and non-uniform: Due to the fast moving speed of vehicles and the extremely uneven distribution of vehicle density on the road, the network topology is constantly changing. 3) The predictability of node movement: The movement of vehicle nodes is limited by factors such as road structure, traffic laws, vehicle density, traffic conditions, and road speed limits. Comprehensively consider these factors and according to the traveler's social characteristics and historical trajectory information, construct a movement trajectory prediction model. 4) Strong traffic information acquisition and processing capabilities: The development of vehicle-mounted sensor equipment provides support for vehicle-mounted self-organizing network routing to obtain traffic information, including positioning data provided by GPS navigation system, speed and direction information provided by vehicle speed detectors Both can be used as an important basis for routing decisions.
针对不同交通场景和不同传输需求，目前主要的几种VANETs路由协议：1)基于地理位置信息的路由协议：通过GPS设备可以获取车辆节点自身、邻居和目的地的位置，以此为基础做出下一跳选择的路由判断。2)基于移动轨迹信息的路由算法：挖掘车辆的历史行驶轨迹或全球卫星导航(GPS)***，结合当前车辆的行驶路径、位置、速度、方向等信息便可以对车辆未来的行驶路径进行预测。3)基于洪泛控制的机会路由算法：通过复制拷贝的方式来增加同一份数据包的副本数量，并以洪泛的机制将数据包消息副本传递给尽可能多的节点。4)基于历史信息的机会转发算法：统计车辆节点的历史信息以及历史过程中数据包成功投递的概率的评估，有目的性地转发数据包到邻居节点。In view of different traffic scenarios and different transmission requirements, there are currently several main VANETs routing protocols: 1) Routing protocol based on geographic location information: The location of the vehicle node itself, neighbors and destination can be obtained through GPS equipment. Judge the route selected by the next hop. 2) Routing algorithm based on movement trajectory information: mining the historical driving trajectory of the vehicle or global satellite navigation (GPS) system, combining the current driving path, position, speed, direction and other information of the vehicle can predict the future driving path of the vehicle. 3) Opportunistic routing algorithm based on flooding control: Increase the number of copies of the same data packet by copying, and use the flooding mechanism to deliver the copy of the data packet message to as many nodes as possible. 4) Opportunistic forwarding algorithm based on historical information: Count the historical information of vehicle nodes and the evaluation of the probability of successful delivery of data packets in the historical process, and purposefully forward data packets to neighboring nodes.
通过对现有路由方法以及转发机制的分析，传统的路由算法没有考虑到转发节的有效性，以及忽视了中继节点的传递潜能、传输可靠性、节点自身资源利用情况等的不同而导致节点的差异性。盲目且均等的分发消息副本数量，该算法在可划分区域的网络中，消息的转发效率较低。Through the analysis of existing routing methods and forwarding mechanisms, the traditional routing algorithm does not consider the effectiveness of the forwarding node, and ignores the transfer potential of the relay node, transmission reliability, and the node’s own resource utilization, which leads to the node The difference. Blindly and equally distribute the number of message copies. This algorithm has low message forwarding efficiency in a network that can be divided into areas.
发明内容Summary of the invention
针对现有技术中存在的不足，本发明的目的在于，提供一种车联网中基于节点效能的机会转发方法，解决现有技术消息转发效率低的技术问题。In view of the deficiencies in the prior art, the purpose of the present invention is to provide an opportunity forwarding method based on node efficiency in the Internet of Vehicles, and solve the technical problem of low message forwarding efficiency in the prior art.
为了解决上述技术问题，本申请采用如下技术方案予以实现：In order to solve the above technical problems, this application adopts the following technical solutions to achieve:
一种车联网中基于节点效能的机会转发方法，包括以下步骤：An opportunity forwarding method based on node effectiveness in the Internet of Vehicles includes the following steps:
步骤1，请求车辆节点s将所携带的N个消息副本中的N i个消息副本分配给候选节点i，i＝1,2,...,n，N i≤N；其中，候选节点为请求车辆节点s的通信范围内的所有节点； Step 1. Request the vehicle node s to allocate N i message copies of the carried N message copies to the candidate node i, i=1, 2,...,n, N i ≤N; where the candidate node is Request all nodes within the communication range of the vehicle node s;
步骤2，候选节点i将所接收到的N i个消息副本转发至目的节点d，包括以下步骤： Step 2, the candidate node i N i copies of the received messages forwarded to the destination node d, comprising the steps of:
步骤2.1，将候选节点i作为当前待转发节点；Step 2.1: Use candidate node i as the current node to be forwarded;
步骤2.2，将当前待转发节点遇到的第一个节点作为当前中继节点，若当前中继节点的运动方向与目的节点d的运动方向的夹角小于90°，则执行步骤2.4；否则，执行步骤2.3；Step 2.2, take the first node encountered by the current node to be forwarded as the current relay node. If the angle between the movement direction of the current relay node and the movement direction of the destination node d is less than 90°, go to step 2.4; otherwise, Perform step 2.3;
步骤2.3，若当前中继节点的相遇指数大于当前待转发节点的相遇指数，执行步骤2.4；Step 2.3, if the encounter index of the current relay node is greater than the encounter index of the current node to be forwarded, perform step 2.4;
步骤2.4，当前待转发节点将N i个消息副本转发给当前中继节点； Step 2.4, the current node to be forwarded to forward a copy of the message to the N i th relay node of the current;
步骤2.5，将当前中继节点作为当前待转发节点，重复步骤2.2至步骤2.4，直至N i个消息副本转发给目的节点d。 Step 2.5, the current relay node as a current node to be forwarded, step 2.2 through step 2.4 is repeated until the N i th forward a copy of the message to the destination node d.
进一步地，所述步骤1中请求车辆节点s将N i个消息副本分配给候选节点i，包括以下步骤： Further, the step of requesting a vehicle assigned to the candidate node s to node i N i copies of messages, comprising the steps of:
步骤1.1，通过公式一计算候选节点i的传输消息效用值U i： Step 1.1, calculate the transmission message utility value U i of candidate node i by formula 1:
Figure PCTCN2019099807-appb-000001
Figure PCTCN2019099807-appb-000001
其中，ω表示可调参数，ω∈(0,1)；Among them, ω represents adjustable parameters, ω∈(0,1);
Figure PCTCN2019099807-appb-000002
表示候选节点i与目的节点d在T时间段内的连接效用值；
Figure PCTCN2019099807-appb-000003
Figure PCTCN2019099807-appb-000004
表示候选节点i与目的节点d在T时间段内的连接次数
Figure PCTCN2019099807-appb-000002
Represents the connection utility value of the candidate node i and the destination node d in the time period T;
Figure PCTCN2019099807-appb-000003
Figure PCTCN2019099807-appb-000004
Represents the number of connections between candidate node i and destination node d in time period T
Figure PCTCN2019099807-appb-000005
表示n个候选节点在T时间段内与目的节点d的连接次数，l表示连接到节点的个数；
Figure PCTCN2019099807-appb-000005
Represents the number of connections between n candidate nodes and the destination node d in the T time period, and l represents the number of nodes connected to;
Figure PCTCN2019099807-appb-000006
表示候选节点i将消息传递到目的节点d的概率预测效用值；
Figure PCTCN2019099807-appb-000007
其中P(i,d)表示候选节点i与目的节点d的相遇概率预测值，P(j,d)表示候选节点j与目的节点d的相遇概率预测值，
Figure PCTCN2019099807-appb-000008
表示n个候选节点与目的节点d的相遇概率预测值的总和；
Figure PCTCN2019099807-appb-000006
Indicates the predicted utility value of the probability that the candidate node i will deliver the message to the destination node d;
Figure PCTCN2019099807-appb-000007
Where P(i,d) represents the predicted value of the probability of encounter between the candidate node i and the destination node d, P(j,d) represents the predicted value of the probability of encounter between the candidate node j and the destination node d,
Figure PCTCN2019099807-appb-000008
Represents the sum of the predicted values of the encounter probability of n candidate nodes and the destination node d;
步骤1.2，根据候选节点i的传输消息效用值U i，通过公式二得到请求车辆节点s分配给候选节点i的消息副本数N i： Step 1.2 The transmission of the message utility value of the U-candidate node i, i, s allocated node to a vehicle number of message copies candidate node N i i obtained by requesting formula 2:
Figure PCTCN2019099807-appb-000009
Figure PCTCN2019099807-appb-000009
其中，U s表示请求车辆节点s的传输消息效用值。 Among them, U s represents the utility value of the transmission message of the requested vehicle node s.
进一步地，通过公式三计算候选节点i与目的节点d的相遇概率预测值P(i,d)：Further, the predicted value P(i,d) of the probability of encounter between the candidate node i and the destination node d is calculated by formula 3:
P(i,d)＝P(i,d) old+[(1-P(i,d) old)×P init×k μ]    公式三 P(i,d)=P(i,d) old +[(1-P(i,d) old )×P init ×k μ ] formula three
其中，P(i,d) old为候选转发节点r和目的节点d上一次更新的相遇概率值；k为相遇持续时间内对转发概率的影响因子，k>1；P init为初始常量，0≤P init≤1； Among them, P(i,d) old is the last updated encounter probability value of the candidate forwarding node r and the destination node d; k is the influence factor on the forwarding probability during the encounter duration, k>1; P init is the initial constant, 0 ≤P init ≤1;
μ为节点间相遇持续时间影响因子，
Figure PCTCN2019099807-appb-000010
Figure PCTCN2019099807-appb-000011
为候选节点i和目的节点d相遇q次的总时长；
Figure PCTCN2019099807-appb-000012
为候选节点i与车联网中除目的节点d以外的其他节点之间相遇的总时长；
Figure PCTCN2019099807-appb-000013
为目的节点d与车联网中除目的节点d以外的其他节点之间相遇的总时长。 μ is the influencing factor of the duration of encounter between nodes,
Figure PCTCN2019099807-appb-000010
Figure PCTCN2019099807-appb-000011
Is the total length of time the candidate node i and the destination node d meet q times;
Figure PCTCN2019099807-appb-000012
Is the total time of the encounter between the candidate node i and other nodes in the Internet of Vehicles except the destination node d;
Figure PCTCN2019099807-appb-000013
It is the total duration of the encounter between the destination node d and other nodes in the Internet of Vehicles except the destination node d.
进一步地，通过公式四计算所述步骤2.3中当前中继节点的相遇指数
Figure PCTCN2019099807-appb-000014
Further, the encounter index of the current relay node in step 2.3 is calculated by formula 4
Figure PCTCN2019099807-appb-000014
Figure PCTCN2019099807-appb-000015
Figure PCTCN2019099807-appb-000015
其中，Hops (i,d)表示当前中继节点i到目的节点d所经历的跳数；
Figure PCTCN2019099807-appb-000016
表示当前中继节点在过去的单位时间T内所接触到的节点数；
Figure PCTCN2019099807-appb-000017
表示当前中继节点在过去的单位时间T内所接触到的节点数均值。 Among them, Hops (i, d) represents the number of hops experienced by the current relay node i to the destination node d;
Figure PCTCN2019099807-appb-000016
Indicates the number of nodes contacted by the current relay node in the past unit time T;
Figure PCTCN2019099807-appb-000017
Represents the average number of nodes that the current relay node has contacted in the past unit time T.
本发明与现有技术相比，有益的技术效果是：Compared with the prior art, the present invention has the following beneficial technical effects:
1、本发明通过节点之间携带的多跳信息以及对历史运动过程的统计信息选择合适的中继节点进行转发，以此方式快速的实现移动车辆节点之间数据传输与信息共享。1. The present invention selects a suitable relay node for forwarding through the multi-hop information carried between nodes and the statistical information of the historical movement process, so as to quickly realize data transmission and information sharing between mobile vehicle nodes.
2、本发明以节点的传输效能动态分配消息副本数量，不仅可以更好地提升消息的成功传输效率，也可避免传递能力较弱的节点传输消息产生的网络资源浪费。2. The present invention dynamically allocates the number of message copies based on the transmission efficiency of the node, which not only can better improve the successful transmission efficiency of the message, but also can avoid the waste of network resources caused by the transmission of messages by nodes with weaker transmission capabilities.
3、本发明引入车辆节点的概率预测信息、地理位置信息、节点的运动属性以及相遇指数作为判断依据，选择更适合的中继节点，以提高车联网中的消息传输率、降低消息传输时延、网络负载和平均跳数等网络链路整体性能。3. The present invention introduces the probability prediction information of the vehicle node, the geographic location information, the movement attribute of the node and the encounter index as the judgment basis, and selects a more suitable relay node to improve the message transmission rate in the Internet of Vehicles and reduce the message transmission delay The overall performance of the network link such as network load and average number of hops.
附图说明Description of the drawings
图1为节点间相遇连接时间过程图；Figure 1 is a time process diagram of encounter and connection between nodes;
图2为Spray阶段数据转发流程图；Figure 2 is a flow chart of data forwarding in the Spray phase;
图3为预测值比较过程示意图；Figure 3 is a schematic diagram of the prediction value comparison process;
图4为Wait阶段数据转发流程图；Figure 4 is a flowchart of data forwarding in the Wait phase;
图5为节点运动场景示意图；Figure 5 is a schematic diagram of a node motion scene;
图6为节点运动方向示意图。Figure 6 is a schematic diagram of the movement direction of the node.
以下结合附图和实施例对本发明的具体内容作进一步详细解释说明。The specific content of the present invention will be further explained in detail below with reference to the drawings and embodiments.
具体实施方式Detailed ways
以下给出本发明的具体实施例，需要说明的是本发明并不局限于以下具体实施例，凡在本申请技术方案基础上做的等同变换均落入本发明的保护范围。Specific embodiments of the present invention are given below. It should be noted that the present invention is not limited to the following specific embodiments, and all equivalent transformations made on the basis of the technical solutions of the present application fall within the protection scope of the present invention.
实施例：Examples:
本实施例给出一种车联网中基于节点效能的机会转发方法，本发明中请求车辆节点s产生消息并需要将该消息转发至目的节点d，请求车辆节点s可以为车联网中任一车辆节点，包括以下步骤：This embodiment provides an opportunity forwarding method based on node efficiency in the Internet of Vehicles. In the present invention, the vehicle node s is requested to generate a message and needs to forward the message to the destination node d. The requesting vehicle node s can be any vehicle in the Internet of Vehicles. Node, including the following steps:
步骤1，请求车辆节点s将所携带的N个消息副本中的N i个消息副本分配给候选节点i，i＝1,2,...,n，N i≤N；其中，候选节点为请求车辆节点s的通信范围内的所有节点； Step 1. Request the vehicle node s to allocate N i message copies of the carried N message copies to the candidate node i, i=1, 2,...,n, N i ≤N; where the candidate node is Request all nodes within the communication range of the vehicle node s;
本发明中的车联网可以是城市道路交通的车联网网络，其中所有的节点均为车联网网络中的车辆。The Internet of Vehicles in the present invention may be an Internet of Vehicles network of urban road traffic, in which all nodes are vehicles in the Internet of Vehicles network.
如图2所示，包括以下步骤：As shown in Figure 2, it includes the following steps:
步骤1.1，通过公式一计算候选节点i的传输消息效用值U i： Step 1.1, calculate the transmission message utility value U i of candidate node i by formula 1:
Figure PCTCN2019099807-appb-000018
Figure PCTCN2019099807-appb-000018
其中，ω表示可调参数，用于调节两个效用值的相对重要性，ω∈(0,1)；Among them, ω represents an adjustable parameter, which is used to adjust the relative importance of two utility values, ω∈(0,1);
Figure PCTCN2019099807-appb-000019
表示候选节点i与目的节点d在T时间段内的连接效用值；
Figure PCTCN2019099807-appb-000020
Figure PCTCN2019099807-appb-000021
表示候选节点i与目的节点d在T时间段内的连接次数，
Figure PCTCN2019099807-appb-000022
表示n个候选节点在T时间段内与目的节点d的连接次数，l表示连接到节点的个数；
Figure PCTCN2019099807-appb-000019
Represents the connection utility value of the candidate node i and the destination node d in the time period T;
Figure PCTCN2019099807-appb-000020
Figure PCTCN2019099807-appb-000021
Represents the number of connections between candidate node i and destination node d in time period T,
Figure PCTCN2019099807-appb-000022
Represents the number of connections between n candidate nodes and the destination node d in the T time period, and l represents the number of nodes connected to;
Figure PCTCN2019099807-appb-000023
表示候选节点i将消息传递到目的节点d的概率预测效用值；
Figure PCTCN2019099807-appb-000024
其中P(i,d)表示候选节点i与目的节点d的相遇概率预测值，P(j,d)表示候选节点j与目的节点d的相遇概率预测值，
Figure PCTCN2019099807-appb-000025
表示n个候选节点与目的节点d的相遇概率预测值的总和；
Figure PCTCN2019099807-appb-000023
Indicates the predicted utility value of the probability that the candidate node i will deliver the message to the destination node d;
Figure PCTCN2019099807-appb-000024
Where P(i,d) represents the predicted value of the probability of encounter between the candidate node i and the destination node d, P(j,d) represents the predicted value of the probability of encounter between the candidate node j and the destination node d,
Figure PCTCN2019099807-appb-000025
Represents the sum of the predicted values of the encounter probability of n candidate nodes and the destination node d;
通过公式三计算候选节点i与目的节点d的相遇概率预测值P(i,d)：Calculate the predicted value P(i,d) of the probability of encounter between the candidate node i and the destination node d by formula 3:
P(i,d)＝P(i,d) old+[(1-P(i,d) old)×P init×k μ]    公式三 P(i,d)=P(i,d) old +[(1-P(i,d) old )×P init ×k μ ] formula three
其中，P(i,d) old为候选转发节点r和目的节点d上一次更新的相遇概率值；k为相遇持续时间内对转发概率的影响因子，k>1；P init为初始常量，0≤P init≤1； Among them, P(i,d) old is the last updated encounter probability value of the candidate forwarding node r and the destination node d; k is the influence factor on the forwarding probability during the encounter duration, k>1; P init is the initial constant, 0 ≤P init ≤1;
μ为节点间相遇持续时间影响因子，
Figure PCTCN2019099807-appb-000026
Figure PCTCN2019099807-appb-000027
为候选节点i和目的节点d相遇q次的总时长；
Figure PCTCN2019099807-appb-000028
为候选节点i与车联网中除目的节点d以外的其他节点之间相遇的总时长；
Figure PCTCN2019099807-appb-000029
为目的节点d与车联网中除目的节点d以外的其他节点之间相遇的总时长。 μ is the influencing factor of the duration of encounter between nodes,
Figure PCTCN2019099807-appb-000026
Figure PCTCN2019099807-appb-000027
Is the total length of time the candidate node i and the destination node d meet q times;
Figure PCTCN2019099807-appb-000028
Is the total time of the encounter between the candidate node i and other nodes in the Internet of Vehicles except the destination node d;
Figure PCTCN2019099807-appb-000029
It is the total duration of the encounter between the destination node d and other nodes in the Internet of Vehicles except the destination node d.
图1说明了相遇持续时间表示的是两节点建立的通信链路能够保持持续连接状态的时间，该设置是允许两个节点彼此发送数据包的最小相遇连接时间，从而防止两个节点在没有足够通信时间的情况下开始向其他车辆节点发送数据包。Figure 1 illustrates that the encounter duration represents the time that the communication link established by two nodes can maintain a continuous connection state. This setting is the minimum encounter connection time that allows two nodes to send data packets to each other, thereby preventing two nodes from not having enough time In the case of communication time, start sending data packets to other vehicle nodes.
本发明中，如图3.5(a)，如果节点的相遇持续连接时间小于该算法定义的最小阈值
Figure PCTCN2019099807-appb-000030
则该连接节点被立即丢弃，请求车辆节点继续移动并选择具 有较高估计相遇接触时间的邻居节点发送数据包消息，如果没有车辆节点的估计相遇接触时间大于或等于最小阈值
Figure PCTCN2019099807-appb-000031
则节点i返回空闲状态。如图3.5(b)所示，节点间的连接时间大于最小阈值
Figure PCTCN2019099807-appb-000032
则可以建立相对稳定的通信链接。如图3.5(c)所示，节点间的连接时间相对较长，该节点在历史过程中能够满足通信链路可靠性和稳定性。 In the present invention, as shown in Figure 3.5(a), if the node’s meeting and continuous connection time is less than the minimum threshold defined by the algorithm
Figure PCTCN2019099807-appb-000030
Then the connected node is immediately discarded, and the vehicle node is requested to continue moving and select a neighbor node with a higher estimated contact time to send a data packet message. If the estimated contact time of no vehicle node is greater than or equal to the minimum threshold
Figure PCTCN2019099807-appb-000031
Then node i returns to the idle state. As shown in Figure 3.5(b), the connection time between nodes is greater than the minimum threshold
Figure PCTCN2019099807-appb-000032
Then a relatively stable communication link can be established. As shown in Figure 3.5(c), the connection time between nodes is relatively long, and the node can meet the reliability and stability of the communication link in the historical process.
步骤1.2，根据候选节点i的传输消息效用值U i，通过公式二得到请求车辆节点s分配给候选节点i的消息副本数N i： Step 1.2 The transmission of the message utility value of the U-candidate node i, i, s allocated node to a vehicle number of message copies candidate node N i i obtained by requesting formula 2:
Figure PCTCN2019099807-appb-000033
Figure PCTCN2019099807-appb-000033
其中，U s表示请求车辆节点s的传输消息效用值。 Among them, U s represents the utility value of the transmission message of the requested vehicle node s.
本发明在消息传输的过程中，考虑到车联网环境的节点具有移动性，中继节点的传递潜能、传输可靠性、节点自身资源利用情况等的不同而导致节点的差异性。由于Spray and Wait路由机制的Spray阶段，忽视了每个节点传输消息的能力不同、错综复杂的网络拓扑结构、节点的历史相遇信息等因素，使得该传输过程盲目且不够灵活。所以，综合考虑车辆节点的基于相遇连接时间的概率预测效用值、以及对节点在历史过程中的连接统计效用值，共同评价节点的消息传输能力，对于不同的节点区别对待，使得消息副本的分配更加合理高效。尽可能把消息发送给与自身节点能够建立可靠连接以及保持良好通信链路的下一跳节点，从而增强消息传输的有效性。In the process of message transmission, the present invention takes into account the mobility of the nodes in the Internet of Vehicles environment, and the differences in the transfer potential of the relay node, the transmission reliability, the node's own resource utilization, etc. cause the differences of the nodes. Because the Spray phase of the Spray and Wait routing mechanism ignores factors such as the different ability of each node to transmit messages, the intricate network topology, and the historical encounter information of the nodes, the transmission process is blind and not flexible enough. Therefore, comprehensively consider the predicted utility value of the vehicle node based on the probability of the encounter connection time and the statistical utility value of the connection of the node in the historical process, jointly evaluate the message transmission capacity of the node, and treat different nodes differently, so that the distribution of message copies More reasonable and efficient. Send the message as far as possible to the next hop node that can establish a reliable connection with its own node and maintain a good communication link, thereby enhancing the effectiveness of message transmission.
另外，本发明提出一种根据节点传输能力的不同动态分配消息副本数量的机制，在Spray and Wait路由机制的Spray阶段，由于其固定且均等的给相遇节点分发消息副本，该过程没能考虑到相遇节点的差异性。因此，引入节点传输能力的计算模型，通过该模型计算的节点效能值来动态分配其消息副 本的数量。具体的，中继节点传递消息的能力值越大，应该分配给该节点更多的消息副本，改变了原来传统Spray and Wait路由算法在Spray阶段盲目均等的散发机制。本发明充分考虑了链路传输的可靠性和有效性，使该过程中的转发决策更为合理和高效，并以更快的速度完成消息副本的传输。同时，该方法的散发机制使得移动车辆节点能够更好的适应不断动态变化的网络环境。In addition, the present invention proposes a mechanism for dynamically allocating the number of message copies according to the different transmission capabilities of nodes. In the Spray phase of the Spray and Wait routing mechanism, because it distributes message copies to the meeting nodes in a fixed and equal manner, this process fails to take into account The difference of meeting nodes. Therefore, a calculation model of node transmission capacity is introduced, and the number of message copies is dynamically allocated through the node performance value calculated by the model. Specifically, the greater the relay node's ability to deliver messages, the more message copies should be allocated to the node, which changes the original traditional Spray and Wait routing algorithm's blind and equal distribution mechanism in the Spray phase. The present invention fully considers the reliability and effectiveness of link transmission, makes the forwarding decision in the process more reasonable and efficient, and completes the transmission of the message copy at a faster speed. At the same time, the dissemination mechanism of this method enables mobile vehicle nodes to better adapt to the constantly changing network environment.
步骤2，候选节点i将所接收到的N i个消息副本转发至目的节点d，如图4，包括以下步骤： Step 2, the candidate node i N i copies of the received messages forwarded to the destination node d, as shown in FIG 4, comprising the steps of:
步骤2.1，将候选节点i作为当前待转发节点；Step 2.1: Use candidate node i as the current node to be forwarded;
步骤2.2，将当前待转发节点遇到的第一个节点作为当前中继节点，若当前中继节点的运动方向与目的节点d的运动方向的夹角小于90°，则执行步骤2.4；否则，执行步骤2.3；Step 2.2, take the first node encountered by the current node to be forwarded as the current relay node. If the angle between the movement direction of the current relay node and the movement direction of the destination node d is less than 90°, go to step 2.4; otherwise, Perform step 2.3;
如图6中
Figure PCTCN2019099807-appb-000034
为节点j的运动方向、目的节点d的运动方向，其中
Figure PCTCN2019099807-appb-000035
节点j的位置坐标为
Figure PCTCN2019099807-appb-000036
目的节点d的位置坐标为
Figure PCTCN2019099807-appb-000037
则节点j与目的节点d的运动位置夹角为θ，
Figure PCTCN2019099807-appb-000038
As shown in Figure 6
Figure PCTCN2019099807-appb-000034
Is the movement direction of node j and the movement direction of destination node d, where
Figure PCTCN2019099807-appb-000035
The position coordinate of node j is
Figure PCTCN2019099807-appb-000036
The location coordinates of the destination node d are
Figure PCTCN2019099807-appb-000037
Then the angle between the movement position of node j and destination node d is θ,
Figure PCTCN2019099807-appb-000038
本实施例中的运动方向还可以为运动速度等运动属性。The movement direction in this embodiment may also be movement attributes such as movement speed.
步骤2.3，若当前中继节点的相遇指数大于当前待转发节点的相遇指数，执行步骤2.4；若当前待转发节点所遇到的当前中继节点均不满足上述两个条件，则当前待转发节点携带的消息副本就转发失败。Step 2.3, if the encounter index of the current relay node is greater than the encounter index of the current node to be forwarded, proceed to step 2.4; if the current relay node encountered by the current node to be forwarded does not meet the above two conditions, then the current node to be forwarded The carried copy of the message fails to be forwarded.
通过公式四计算所述步骤2.3中当前中继节点的相遇指数
Figure PCTCN2019099807-appb-000039
Calculate the encounter index of the current relay node in step 2.3 by formula 4
Figure PCTCN2019099807-appb-000039
Figure PCTCN2019099807-appb-000040
Figure PCTCN2019099807-appb-000040
其中，Hops (i,d)表示当前中继节点i到目的节点d所经历的跳数；
Figure PCTCN2019099807-appb-000041
表示 当前中继节点在过去的单位时间T内所接触到的节点数；
Figure PCTCN2019099807-appb-000042
表示当前中继节点在过去的单位时间T内所接触到的节点数均值，T表示节点相遇指数更新时间。 Among them, Hops (i, d) represents the number of hops experienced by the current relay node i to the destination node d;
Figure PCTCN2019099807-appb-000041
Indicates the number of nodes contacted by the current relay node in the past unit time T;
Figure PCTCN2019099807-appb-000042
Represents the average number of nodes that the current relay node has contacted in the past unit time T, and T represents the update time of the node encounter index.
步骤2.4，当前待转发节点将N i个消息副本转发给当前中继节点； Step 2.4, the current node to be forwarded to forward a copy of the message to the N i th relay node of the current;
步骤2.5，将当前中继节点作为当前待转发节点，重复步骤2.2至步骤2.4，直至N i个消息副本转发给目的节点d。 Step 2.5, the current relay node as a current node to be forwarded, step 2.2 through step 2.4 is repeated until the N i th forward a copy of the message to the destination node d.
本发明通过车辆节点的节点运动属性和相遇指数来建立消息的传输选择模型，使得原来被动等待目的节点的方式变为主动寻找下一跳节点，即当前节点在其通信范围内存在邻居节点时，选择更有效的中继节点将消息更快速的传输到目的地。特别的，数据转发的决策中移动车辆的运动属性非常重要，所以利用车联网中的车辆节点的运动特性可以有效地提高数据包的传输效率，降低消息转发时延。其中节点相遇指数作为节点运动属性的补充，如果节点的运动属性不符合要求，则进行节点相遇指数判断以增加中继节点的选择维度。Wait阶段的数据转发模型具体过如图5所示。The present invention establishes a message transmission selection model based on the node motion attributes and the encounter index of the vehicle node, so that the original way of passively waiting for the destination node becomes actively looking for the next hop node, that is, when the current node has a neighbor node in its communication range, Choose a more efficient relay node to transmit the message to the destination faster. In particular, the motion attributes of moving vehicles are very important in the data forwarding decision. Therefore, using the motion characteristics of vehicle nodes in the Internet of Vehicles can effectively improve the transmission efficiency of data packets and reduce message forwarding delay. The node encounter index is used as a supplement to the node's motion attributes. If the node's motion attributes do not meet the requirements, the node encounter index is judged to increase the choice dimension of the relay node. The data forwarding model in the Wait phase is shown in Figure 5.

Claims (4)

  1. 一种车联网中基于节点效能的机会转发方法，其特征在于，包括以下步骤：An opportunity forwarding method based on node effectiveness in the Internet of Vehicles is characterized in that it comprises the following steps:
    步骤1，请求车辆节点s将所携带的N个消息副本中的N i个消息副本分配给候选节点i，i＝1,2,...,n，N i≤N；其中，候选节点为请求车辆节点s的通信范围内的所有节点； Step 1. Request the vehicle node s to allocate N i message copies of the carried N message copies to the candidate node i, i=1, 2,...,n, N i ≤N; where the candidate node is Request all nodes within the communication range of the vehicle node s;
    步骤2，候选节点i将所接收到的N i个消息副本转发至目的节点d，包括以下步骤： Step 2, the candidate node i N i copies of the received messages forwarded to the destination node d, comprising the steps of:
    步骤2.1，将候选节点i作为当前待转发节点；Step 2.1: Use candidate node i as the current node to be forwarded;
    步骤2.2，将当前待转发节点遇到的第一个节点作为当前中继节点，若当前中继节点的运动方向与目的节点d的运动方向的夹角小于90°，则执行步骤2.4；否则，执行步骤2.3；Step 2.2, take the first node encountered by the current node to be forwarded as the current relay node. If the angle between the movement direction of the current relay node and the movement direction of the destination node d is less than 90°, go to step 2.4; otherwise, Perform step 2.3;
    步骤2.3，若当前中继节点的相遇指数大于当前待转发节点的相遇指数，执行步骤2.4；Step 2.3, if the encounter index of the current relay node is greater than the encounter index of the current node to be forwarded, perform step 2.4;
    步骤2.4，当前待转发节点将N i个消息副本转发给当前中继节点； Step 2.4, the current node to be forwarded to forward a copy of the message to the N i th relay node of the current;
    步骤2.5，将当前中继节点作为当前待转发节点，重复步骤2.2至步骤2.4，直至N i个消息副本转发给目的节点d。 Step 2.5, the current relay node as a current node to be forwarded, step 2.2 through step 2.4 is repeated until the N i th forward a copy of the message to the destination node d.
  2. 如权利要求1所述的车联网中基于节点效能的机会转发方法，其特征在于，所述步骤1中请求车辆节点s将N i个消息副本分配给候选节点i，包括以下步骤： The method of opportunity forwarding based on node effectiveness in the Internet of Vehicles according to claim 1, wherein the requesting vehicle node s to allocate N i message copies to candidate node i in said step 1 comprises the following steps:
    步骤1.1，通过公式一计算候选节点i的传输消息效用值U i： Step 1.1, calculate the transmission message utility value U i of candidate node i by formula 1:
    Figure PCTCN2019099807-appb-100001
    Figure PCTCN2019099807-appb-100001
    其中，ω表示可调参数，ω∈(0,1)；Among them, ω represents adjustable parameters, ω∈(0,1);
    Figure PCTCN2019099807-appb-100002
    表示候选节点i与目的节点d在T时间段内的连接效用值；
    Figure PCTCN2019099807-appb-100003
    表示候选节点i与目的节点d在T时间段内的连接次数
    Figure PCTCN2019099807-appb-100002
    Represents the connection utility value of the candidate node i and the destination node d in the time period T;
    Figure PCTCN2019099807-appb-100003
    Represents the number of connections between candidate node i and destination node d in time period T
    Figure PCTCN2019099807-appb-100004
    表示n个候选节点在T时间段内与目的节点d的连接次数，l表示连接到节点的个数；
    Figure PCTCN2019099807-appb-100004
    Represents the number of connections between n candidate nodes and the destination node d in the T time period, and l represents the number of nodes connected to;
    Figure PCTCN2019099807-appb-100005
    表示候选节点i将消息传递到目的节点d的概率预测效用值；
    Figure PCTCN2019099807-appb-100006
    其中P(i,d)表示候选节点i与目的节点d的相遇概率预测值，P(j,d)表示候选节点j与目的节点d的相遇概率预测值，
    Figure PCTCN2019099807-appb-100007
    表示n个候选节点与目的节点d的相遇概率预测值的总和；
    Figure PCTCN2019099807-appb-100005
    Indicates the predicted utility value of the probability that the candidate node i will deliver the message to the destination node d;
    Figure PCTCN2019099807-appb-100006
    Where P(i,d) represents the predicted value of the probability of encounter between the candidate node i and the destination node d, P(j,d) represents the predicted value of the probability of encounter between the candidate node j and the destination node d,
    Figure PCTCN2019099807-appb-100007
    Represents the sum of the predicted values of the encounter probability of n candidate nodes and the destination node d;
    步骤1.2，根据候选节点i的传输消息效用值U i，通过公式二得到请求车辆节点s分配给候选节点i的消息副本数N i： Step 1.2 The transmission of the message utility value of the U-candidate node i, i, s allocated node to a vehicle number of message copies candidate node N i i obtained by requesting formula 2:
    Figure PCTCN2019099807-appb-100008
    Figure PCTCN2019099807-appb-100008
    其中，U s表示请求车辆节点s的传输消息效用值。 Among them, U s represents the utility value of the transmission message of the requested vehicle node s.
  3. 如权利要求2所述的车联网中基于节点效能的机会转发方法，其特征在于，通过公式三计算候选节点i与目的节点d的相遇概率预测值P(i,d)：The method of opportunity forwarding based on node effectiveness in the Internet of Vehicles according to claim 2, characterized in that the predicted value P(i,d) of the probability of encounter between the candidate node i and the destination node d is calculated by formula 3:
    P(i,d)＝P(i,d) old+[(1-P(i,d) old)×P init×k μ]    公式三 P(i,d)=P(i,d) old +[(1-P(i,d) old )×P init ×k μ ] formula three
    其中，P(i,d) old为候选转发节点r和目的节点d上一次更新的相遇概率值；k为相遇持续时间内对转发概率的影响因子，k>1；P init为初始常量，0≤P init≤1； Among them, P(i,d) old is the last updated encounter probability value of the candidate forwarding node r and the destination node d; k is the influence factor on the forwarding probability during the encounter duration, k>1; P init is the initial constant, 0 ≤P init ≤1;
    μ为节点间相遇持续时间影响因子，
    Figure PCTCN2019099807-appb-100009
    Figure PCTCN2019099807-appb-100010
    为候选节点i和目的节点d相遇q次的总时长；
    Figure PCTCN2019099807-appb-100011
    为候选节点i与车联网中除目的节点d以外的其他节点之间相遇的总时长；
    Figure PCTCN2019099807-appb-100012
    为目的节点d与车联网中除目的节点d以外的其他节点之间相遇的总时长。     μ is the influencing factor of the duration of encounter between nodes,
    Figure PCTCN2019099807-appb-100009
    Figure PCTCN2019099807-appb-100010
    Is the total length of time the candidate node i and the destination node d meet q times;
    Figure PCTCN2019099807-appb-100011
    Is the total time of the encounter between the candidate node i and other nodes in the Internet of Vehicles except the destination node d;
    Figure PCTCN2019099807-appb-100012
    It is the total time of the encounter between the destination node d and other nodes in the Internet of Vehicles except the destination node d.
  4. 如权利要求1所述的车联网中基于节点效能的机会转发方法，其特征在于，通过公式四计算所述步骤2.3中当前中继节点的相遇指数
    Figure PCTCN2019099807-appb-100013
    The method for forwarding opportunities based on node effectiveness in the Internet of Vehicles according to claim 1, wherein the encounter index of the current relay node in step 2.3 is calculated by formula 4
    Figure PCTCN2019099807-appb-100013
    Figure PCTCN2019099807-appb-100014
    Figure PCTCN2019099807-appb-100014
    其中，Hops (i,d)表示当前中继节点i到目的节点d所经历的跳数；
    Figure PCTCN2019099807-appb-100015
    表示当前中继节点在过去的单位时间T内所接触到的节点数；
    Figure PCTCN2019099807-appb-100016
    表示当前中继节点在过去的单位时间T内所接触到的节点数均值。     Among them, Hops (i, d) represents the number of hops experienced by the current relay node i to the destination node d;
    Figure PCTCN2019099807-appb-100015
    Indicates the number of nodes contacted by the current relay node in the past unit time T;
    Figure PCTCN2019099807-appb-100016
    Represents the average number of nodes that the current relay node has contacted in the past unit time T.
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