Stable and Energy Efficient Clustering of Wireless Ad-Hoc Networks with LIDAR Algorithm

Abstract

The main objective of clustering in mobile ad-hoc network environments is to identify suitable node representatives, i.e. cluster heads (CHs) to store routing and topology information; CHs should be elected so as to maximize clusters stability, that is to prevent frequent cluster re-structuring. A popular clustering algorithm (LID) suggests CH election based on node IDs (nodes with locally lowest ID value become CHs). Although fast and simple, this method is biased against nodes with low IDs, which are likely to serve as CHs for long periods and are therefore prone to rapid battery exhaustion. Herein, we propose LIDAR, a novel clustering method which represents a major improvement over traditional LID algorithm: node IDs are periodically re-assigned so that nodes with low mobility rate and high energy capacity are assigned low ID values and, therefore, are likely to serve as CHs. Our protocol also greatly reduces control traffic volume of existing algorithms during clustering maintenance phase, while not risking the energy availability of CHs. Simulation results demonstrate the efficiency, scalability and stability of our protocol against alternative approaches.

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