Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach

• Published in: IEEE INFOCOM 2004 Vol. 1; pp. 629 - 640
• Main Authors: Younis, O., Fahmy, S.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway, New Jersey IEEE 2004
• Subjects: Applied sciences; Batteries; Chemical sensors; Computer networks; Energy consumption; Energy efficiency; Exact sciences and technology; Information, signal and communications theory; Intelligent networks; Media Access Protocol; Mobile ad hoc networks; Network topology; Organization and planning of networks (techniques and equipments); Routing protocols; Signal and communications theory; Signal representation. Spectral analysis; Signal, noise; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Performance evaluation; Automatic classification; Wireless telecommunication; Network architecture; Iterative method; Signal classification; Topological structure; Uniform distribution; Power consumption; Simulation; Hybrid model; Load balancing; Localization; Ad hoc network; Distribution network
• ISBN: 0780383559; 9780780383555
• ISSN: 0743-166X; 2641-9874
• DOI: 10.1109/INFCOM.2004.1354534

Prolonged network lifetime, scalability, and load balancing are important requirements for many ad-hoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to 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 O(1) iterations, and does not depend on the 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 the network lifetime and supporting data aggregation.