A mobility based clustering algorithm in MANETs utilizing Learning Automata
Xun Gao · Chinese Control Conference · 2013
There being ample research in cluster-based Media Access Control (MAC) protocols for Mobile Ad Hoc Networks (MANETs) recently makes it necessary having a stable clustering algorithm developed for MANETs. Nodes in MANETs often have highly mobility and sometimes present the characteristic of group mobility. From the innovation perspective, we proposed a clustering algorithm by employing Learning Automata (LA) in a distributed manner considering nodes distance and nodes mobility to produce stable clusters. By utilizing LA nodes can make intelligent and adaptive decisions based on the local information collected in the past time. Compared to another mobility based clustering algorithm, simulation results present us the superior performance of the proposed algorithm.