Energy-efficient Clustering for Wireless Sensor Networks with Unbalanced Traffic Load

Clustering algorithms have been extensively applied for energy conservation in wireless sensor networks (WSNs). Cluster-heads (CHs) play an important role and drain energy more rapidly than other member nodes. Numerous mechanisms to optimize CH selection and cluster formation during the set-up phase have been proposed for extending the stable operation period of the network until any node depletes its energy. However, the existing mechanisms assume that the traffic load contributed by each node is the same, in other words, same amount of data are sent to CH from the member nodes during each scheduled round. This paper assumes the nodes contribute traffic load at different rates, and consequently proposes an energy-efficient clustering algorithm by considering both the residual node energy and the traffic load contribution of each node during the set-up phase. The proposed algorithm makes nodes with more residual energy and less traffic load contribution get more chances to become CHs. Furthermore, clusters are adaptively organized in a way that the deviation of ratio between the total cluster energy and the total cluster traffic load (ETRatio) is limited, in order to balance the energy usage among the clusters. Performance evaluation shows that the proposed algorithm extends the stable operation period of the network significantl