optimizing communications in vehicular ad hoc networks using evolutionary computation and simulation
Broadcasting efficiently in a Vehicular Ad hoc Network (VANET) is a hard task to achieve. An efficient communication algorithm must take into account several aspects such as the neighboring density, the size and shape of the network, the use of the channel, the priority level of the message. Some studies [6, 12, 13] have proposed new solutions of broadcasting on such a network, but it is quite hard to evaluate their performance in various contexts. In order to determine the best repeating situation for each node in the network according to its environment, we developed a tool combining a network simulator (NS2) and an evolutionary algorithm. In this paper, we study four types of context and we tackle the best behavior for each node to determine the right input parameters. These studies are necessary to develop efficient broadcast algorithms in VANET.
broadcast vanet multi-objective evolutionary algorithm flooding context dissemination