Currently, communications in the vehicular ad hoc network (VANET) can be established via both Dedicated Short Range Communication (DSRC) and mobile cellular networks. To make use of existing Long Term Evolution (LTE) network in data transmissions, many methods are proposed to manage VANETs. Grouping the vehicles into clusters and organizing the network by clusters are one of the most universal and most efficacious ways. Since the high mobility of vehicles makes VANETs different from other mobile ad hoc networks (MANETs), the previous cluster-based methods for MANETs may have trouble for VANETs. In this paper, we introduce a center-based clustering algorithm to help self-organized VANETs forming stable clusters and decrease the status change frequency of vehicles on highways and two metrics. A novel Cluster Head (CH) selection algorithm is also proposed to reduce the impact of vehicle motion differences. We also introduce two metrics to improve the security of VANETs. A simulation is conducted to compare our mechanism to some other mechanisms. The results show that our mechanism obtains high stability and lower packet loss rate.
Stability and security are the key directions of VANET (vehicular ad hoc network) research. In order to solve the related problems in VANET, an improved AODV (ad hoc on-demand distance vector) routing protocol based on fuzzy neural network, namely, GSS-AODV (AODV with genetic simulated annealing, security and stability), is proposed. The improved scheme of the protocol analyzes the data in the movement process of the mobile node in VANET, extracts the parameters that affect the link stability, and uses the fuzzy neural network optimized by genetic simulated annealing to calculate the node stability. The improved scheme extracts the main parameters that affect the security of the nodes. After normalization, the fuzzy neural network based on genetic simulated annealing algorithm is used for fuzzy processing, and the node trust value of each node is evaluated. The improved scheme uses node stability and node trust value to control each routing process and dynamically adjusts parameters of the algorithm. The experimental results show that the improved scheme is stable and secure.
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