Distributed Clustering for Scalable, Long-Lived Sensor Networks

Prolonged network lifetime, scalability, and load balancing are important requirements for many adhoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new hybrid energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (Hybrid Energy-Efficient Distributed c1uslcl"ing). that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity (0 its neighbors or node degree. HEED does not make any assumptions about the distribution or density of nodes, or about node capabilities. e.g., location-awareness. The clustering process terminates in 0(1) iterations, and does not depend on ,t~e network topology or size. The protocol incurs low overhead in terms of processing cycles and mesSages exchanged. It also achieves fairly uniform cluster head distribution across the network. A careful selection of the secondary clustering parameter can balance load among cluster heads. Our simulation results demonstrate that HEED outperforms weight-based clustering protocols in terms of several cluster characteristics. We also apply our approach to a simple application to demonstrate its effectiveness in prolonging Ihe network lifetime and supporting data aggregation.