Route method based on crossroads in opportunistic vehicular ad hoc network

Abstract

The invention requests to protect a route method based on crossroads in an opportunistic vehicular ad hoc network. In an urban environment, vehicular ad hoc network nodes move at high speeds, and a topological structure changes frequently. Aimed at the problems that an existing router algorithm has many limits, uniform distribution of nodes in the network is neglected, and a selected router is not the optimum router because both history information and network global information are considered, the invention provides the router method based on the crossroads. When a source node has a data sending request and no router reaches a target node, a plurality of routes from the source node to the target node are firstly searched for and established, then factors influencing performance of road segments and crossroads are respectively considered, the performance of the road segments and the crossroads are comprehensively considered, the performance of each router is analyzed, and under the condition that the global information is considered, the optimum router is selected from the plurality of routes for data transmission, so that the network delivery rate is effectively improved, and the average transmission time delay is lowered.

Description

technical field [0001] The invention relates to a routing method in an opportunistic vehicle-mounted network, in particular to a routing discovery mechanism, a section selection mechanism, a crossroad selection mechanism, and a design considering global information. Background technique [0002] Opportunistic networks (opportunistic networks) are a kind of self-organizing network that does not require a complete path between the source node and the destination node, and uses the encounter opportunities of mobile nodes to realize communication. It is widely used in vehicle communication. The vehicular ad hoc network is called an opportunistic vehicular network. Vehicle Networks (VANETs, ​​VehicularAdHocNetwork) VANET is a new application of mobile ad hoc networks in the field of transportation. The general MANET does not rely on fixed infrastructure to realize the communication of mobile nodes, but VANET is composed of vehicles loaded with wireless communication equipment an...

AI Technical Summary

Problems solved by technology

[0005] However, the existing anchor routing algorithms based on geographic location still have many deficiencies: some routes do not take vehicle node density into account, which may cause data to be transmitted to road sections with relatively sparse node density, resulting in delays in data transmission increase, decrease in delivery rate

[0006] At the same time, in the routing that considers the vehicle node density, the road section with high node density is given priority. However, due to the influence of factors such as traffic lights, vehicles may form clusters at both ends of the road section. The network hole hinders wireless transmission, because it does not consider whether the nodes on the road section are evenly distributed while considering the vehicle density

In addition, when selecting a road segment, only the current situation of the road segment is considered. Due to the frequent topological changes of VANET, this makes the estimation of the road segment not accurate enough. Finally, when selecting the intersection, only the local information near the current intersection is considered, while Does not take into account the global information of the network, which may make the selected route not the best route

[0007] The problem to be solved by the present invention is: routing is an important mechanism for realizing multi-hop transmission in the vehicle network, but there are many limitations in the existing routing algorithm, and there is not much difficulty in establishing the route from the source node to the destination node. Good use of the density information of vehicle nodes on the road section does not accurately estimate the situation of the road section. At the same time, when selecting the intersection sequence, the global information of the network is not considered, resulting in the selected route is not the best route

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