A Dynamic Clustering Algorithm for MANETs by modifying Weighted Clustering Algorithm with Mobility Prediction

Abstract

The multi hop packet radio networks also named mobile ad-hoc networks (MANETs) have a dynamic topology due to the mobility of their nodes. A notable amount of energy is utilized every time a signal is sent and received by a mobile node. Many such signals and power are wasted to update the positional information of the nodes in a wireless scenario. Further bandwidth is also wasted by sending control signals rather than using it effectively for data communication. To minimize this utilization, we propose a modified algorithm that uses Weighted Clustering Algorithm (WCA) for cluster formation and Mobility Prediction for cluster maintenance. Clustering is an effective technique for node management in a MANET. Cluster formation involves election of a mobile node as Cluster head and it controls the other nodes in the newly formed cluster. The connections between nodes and the cluster head changes rapidly in a mobile ad-hoc network. Thus cluster maintenance is also essential. Prediction of mobility based cluster maintenance involves the process of finding out the next position that a mobile node might take based on the previous locations it visited. In this paper we propose to reduce the overhead in communication by predicting mobility of node using linear auto regression and cluster formation.