Dominating set clustering protocols for mobile ad hoc networks

Abstract

A Mobile ad hoc Network (MANET) is a self-configuring, dynamic, multi-hop network composed of mobile nodes that operate without the need of any established infrastructure. The creation of stable, scalable and adaptive clusters with good performance, faster convergence rate and minimal overhead is a challenging task in MANET. This chapter proposes two clustering techniques for MANET, which are (k, r)-Dominating Set-based, weighted and adaptive to changes in the network topology. The set of dominating nodes functions as the clusterhead (CH) to relay the data and control packets. The proposed scenario-based clustering algorithm for MANETs (SCAMs) is a greedy approximation algorithm, whereas the Distributed SCAM (DSCAM) selects the (k, r)-dominating set through a distributed election mechanism. These algorithms achieve variable degree of CH redundancy through the parameter k, which contributes to reliability. Similarly, flexibility in creating variable diameter clusters is achieved with the parameter r. The performance of these algorithms are evaluated through simulation and the results show that these algorithms create stable, scalable and load-balanced clusters with relatively less control overhead in comparison with the existing popular algorithms.