An energy- and proximity-based unequal clustering algorithm for Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are usually constrained energy and bandwidth. Many solutions, like network clustering, have been proposed in order to overcome these limitations. While this solution is deemed efficient, the cluster-heads closer to the base-station would forward more data packets than farther ones, and thus their energy drains at a faster rate. In this paper, we propose an Energy- and Proximity-based Unequal Clustering algorithm (EPUC) to solve this problem. Basically EPUC imposes a condition on the distance among cluster-heads that is adaptively adjusted, so that the inter-cluster-head proximity is smaller as they get closer to the base-station. In addition, the cluster population is set while factoring in the inter-cluster relaying activities in order to balance the load on cluster-heads. We evaluate the performance of EPUC through simulation and confirm its effectiveness of EPUC using network lifetime metrics.