Efficient Load-Balanced Clustering Algorithms for wireless sensor networks

Wireless sensor networks have been receiving increasing attention in recent years due to their potential applications in the establishment of dynamic communications for emergency/rescue operations, disaster relief efforts, and military networks. In this paper, we investigate the problem of grouping the sensor nodes into clusters to enhance the overall scalability of the network. A selected set of nodes, known as gateway nodes, will act as cluster-heads for each cluster and the objective is to balance the load among these gateways. Load-Balanced Clustering increases system stability and improves the communication between the various nodes in the network. We call the problem addressed in this paper as the Load-Balanced Clustering Problem (LBCP). We first show that a special case of LBCP (whereby the traffic load contributed by all sensor nodes are the same) is optimally solvable in polynomial time. We next prove that the general case of LBCP is NP-hard. We then proposed an efficient 32-approximation algorithm for the problem.