Genetic Algorithm Simulated Annealing based clustering strategy in MANET

Abstract

MANET (Mobile Ad Hoc Network) is a collection of wireless mobile nodes forming a temporary computer communication network without the aid of any established infrastructure or centralized administration. MANET is characterized by both highly dynamic network topology and limited energy. This makes the efficiency of MANET depending not only on its control protocol, but also on its topology management and energy management. Clustering Strategy can improve the flexibility and scalability in network management. With graph theory model and genetic annealing hybrid optimization algorithm, this paper proposes a new clustering strategy named GASA (Genetic Algorithm Simulated Annealing). Simulation indicates that this strategy can with lower clustering cost and obtain dynamic balance of topology and load inside the whole network, so as to prolong the network lifetime. © Springer-Verlag Berlin Heidelberg 2005.