VWCA: An efficient clustering algorithm in vehicular ad hoc networks
Vehicular ad hoc networks (VANETs) are appropriate networks that can be used in intelligent transportation systems. Among challenges in VANET, scalability is a critical issue for a network designer. Clustering is one solution for the scalability problem and is vital for efficient resource consumption and load balancing in large scale networks. As our first algorithm, we propose a novel clustering algorithm, vehicular clustering based on the weighted clustering algorithm (VWCA) that takes into consideration the number of neighbors based on dynamic transmission range, the direction of vehicles, the entropy, and the distrust value parameters. These parameters can increase stability and connectivity and can reduce overhead in network. On the other hand, transmission range of a vehicle is important for forwarding and receiving messages. When a fixed transmission range mechanism is used in VANET, it is likely that vehicles are not located in the range of their neighbors. This is because of the high-rate topology changes and high variability in vehicles density. Thus, we propose an adaptive allocation of transmission range (AATR) technique as our second algorithm, where hello messages and density of traffic around vehicles are used to adaptively adjust the transmission range among them. Finally, we propose a monitoring of malicious vehicle (MMV) algorithm as our third algorithm to determine a distrust value for each vehicle used in the VWCA. The effectiveness of the proposed algorithms is illustrated in a highway scenario.
clustering vehicular ad hoc networks dynamic transmission range connectivity monitoring attackers