VCA: An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks
Min Qin (University of Southern California, USA)
Roger Zimmermann (University of Southern California, USA)
Abstract: Clustering provides an effective mechanism for energy-efficient data delivery in wireless sensor networks. To reduce communication cost, most clustering algorithms rely on a sensor's local properties in electing cluster heads. They often result in unsatisfactory cluster formations, which may cause the network to suffer from load imbalance or extra energy consumption. In this paper, we propose a novel Voting-based Clustering Algorithm (VCA) for energy-efficient data dissemination in wireless sensor networks. This new approach lets sensors vote for their neighbors to elect suitable cluster heads. VCA is completely distributed, location-unaware and independent of network size and topology. It combines load balancing, energy and topology information together by using very simple voting mechanisms. Simulation results show that VCA can reduce the number of clusters by 5-25% and prolong the lifetime of a sensor network by 10-30% over that of existing energy-efficient clustering protocols.
Keywords: cluster head, clustering, data aggregation, energy-efficient, sensor network, voting
Categories: C.2.2, C.2.4