A VANETs routing algorithm based on Euclidean distance clustering

Abstract

Routing is a challenging task in the ad hoc networks, especially in vehicular ad hoc networks (VANETs) where the network topology changes fast and frequently. Since the nodes in VANETs are vehicles, which can easily provide the required power to run GPS receiver to get the accurate information of their position, the position-based routing is found to be a very promising routing strategy for VANETs. In this paper we present a clustering routing algorithm for VANETs. The clustering method is based on the Euclidean distance, which uses the position information to divide the vehicles into clusters. Furthermore, only the same direction vehicles can be divided into the same cluster. To reduce the flooding of the routing control message and increase the stability of the route, the routing discovery is also restricted by the vehicle's driving direction. We implement the routing algorithm in NS2 and compare it with AODV, the simulation results show that in the same VANETs environment, the algorithm not only generate fewer routing control overhead, but also maintain stable route to transfmit more data packets.