Efficient clustering for improving network performance in wireless sensor networks

Authors:
Tal Anker;Danny Bickson;Danny Dolev;Bracha Hod
Affiliations:
The Hebrew University of Jerusalem, Israel and Marvell Semiconductor, CA;The Hebrew University of Jerusalem, Israel;The Hebrew University of Jerusalem, Israel;The Hebrew University of Jerusalem, Israel
Venue:
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Year:
2008

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Abstract

Clustering is an important mechanism in large multi-hop wireless sensor networks for obtaining scalability, reducing energy consumption and achieving better network performance. Most of the research in this area has focused on energy-efficient solutions, but has not thoroughly analyzed the network performance, e.g. in terms of data collection rate and time. The main objective of this paper is to provide a useful fully-distributed inference algorithm for clustering, based on belief propagation. The algorithm selects cluster heads, based on a unique set of global and local parameters, which finally achieves, under the energy constraints, improved network performance. Evaluation of the algorithm implementation shows an increase in throughput in more than 40% compared to HEED scheme. This advantage is expressed in terms of network reliability, data collection quality and transmission cost.