Research On Routing Protocol In VANET

In recent years,with the continuous development of intelligent transportation system,security information services,auxiliary driving,entertainment services and other applications have been achieved.As the core content of intelligent transportation system,VANET has gradually become the hotspot.The routing algorithm has always been the focus of the vehicular ad hoc networks research.Based on the characteristics of VANET,this paper improves the routing algorithm for some problems existing in the VANET routing algorithm,and simulates the improved routing algorithm.The AODV routing algorithm uses the hop count as the basis for determining the quality of the route,without taking into account the stability of the communication link,which may result in frequent interruption of the link due to the poor quality of the selected link.In view of this problem,the vehicle reliability model is improved by combining the characteristics of vehicle node movement in the vehicle network,Using fuzzy logic to improve the inter-link quality prediction method,And improve the AODV algorithm using the improved routing reliability model to obtain the reliable routing algorithm FR-AODV based on fuzzy reasoning.By analyzing the QLAODV algorithm based on Q-learning,it is pointed out that the QLAODV algorithm is affected by the number of nodes,which will lead to the slow convergence of the algorithm due to the large state space.Combined with the advantages of clustering routing algorithm,the use of virtual grid way to cluster the network,Taking the cluster as the state space of Q-learning to improve the convergence rate and accuracy of the algorithm and reduce the influence of scene size on the routing algorithm.By considering the number of nodes within the cluster and the movement state of the node affect the cluster head online learning process,help the algorithm to establish a more stable route in the process of routing discovery.The paper analyzes the problem of network load in the VANET.Considering the node load and the channel load,the improved node load measurement method is given,and the routing algorithm is improved by Q-learning to realize the load balancing of the network.And the congestion control mechanism is added to the algorithm to avoid the phenomenon that the heavy network nodes are involved in the new route and cause the network to become congested.Finally,the simulation result shows that the improved routing algorithm can effectively deal with the vehicle network environment compared with other contrast algorithms.