Distributed mobility prediction-based weighted clustering algorithm for MANETs

Authors:
Vincent Bricard-Vieu;Noufissa Mikou
Affiliations:
LIRSA, Faculté des Sciences Mirande, Dijon Cedex;LIRSA, Faculté des Sciences Mirande, Dijon Cedex
Venue:
ICOIN'05 Proceedings of the 2005 international conference on Information Networking: convergence in broadband and mobile networking
Year:
2005

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Abstract

In this paper, we propose a new distributed Mobility Prediction based Weighted Clustering Algorithm based on an on-demand distributed clustering algorithm for multi-hop packet radio networks. These types of networks, also known as mobile ad hoc networks (MANETs) are dynamic in nature due to the mobility of the nodes. The association and dissociation of nodes to and from clusters perturb the stability of the network topology, and hence reconfiguration of the system is often unavoidable. However, it is vital to keep the topology stable as long as possible. The nodes called cluster-heads form a dominant set and determine the topology and its stability. Simulation experiments are conducted to evaluate performances of our algorithm and compare them to those of the weighted clustering algorithm (WCA), which does not consider prediction. Results show that our algorithm performs better than WCA, in terms of updates of the dominant set, handovers of a node between two clusters and average number of clusters in a dominant set.