A Message-Efficient, Distributed Clustering Algorithm for Wireless Sensor and Actor Networks

Lifetime of sensor nodes determines lifetime of the network and is crucial for the sensing capability. Among the important techniques proposed for prolonging the network lifetime by exploiting redundant deployment is using hierarchical architecture or clustering. However, the primary drawback of hierarchical control is the control message overhead; it is essential that the overhead does not dominate the network operations cost. The clustering algorithm should also scale to the network sizes and the nodes that are awake at any point in time must preserve the desired sensing coverage of the entire network utilizing the redundant deployment. Also, it has been shown that in sensor networks, a fundamental tradeoff exists between energy and latency for data delivery (Y. Yu et al., 2004). If clustering should lead to efficient MAC and routing protocols it could effectively address the real-time requirements posed by WSAN. The principle contributions of this paper are as follows. We propose an extremely lightweight scalable clustering algorithm for clustering in WSN. Inspired by the cellular infrastructure model, we produced clusters of bounded geographic size (given a certain node distribution density this guarantees a bound on the number of nodes in a cluster as well), handles perturbations in the network locally in space and in time. The novelty of the algorithm lies in its deterministic operation to optimally exploit the redundant deployment and produce balanced clusters while retaining the desired sensing coverage with minimum possible control overhead. Extensive simulation has been conducted and results are presented to show the superiority of our algorithm