1st Annual Conference on Broadband Networks

Research Article

Design and analysis of a fast local clustering service for wireless sensor networks

  • @INPROCEEDINGS{10.1109/BROADNETS.2004.30,
        author={Murat Demirbas and Anish Arora and Vineet Mittal and Vinod Kulathumani},
        title={Design and analysis of a fast local clustering service for wireless sensor networks},
        proceedings={1st Annual Conference on Broadband Networks},
        publisher={IEEE},
        proceedings_a={BROADNETS},
        year={2004},
        month={12},
        keywords={},
        doi={10.1109/BROADNETS.2004.30}
    }
    
  • Murat Demirbas
    Anish Arora
    Vineet Mittal
    Vinod Kulathumani
    Year: 2004
    Design and analysis of a fast local clustering service for wireless sensor networks
    BROADNETS
    IEEE
    DOI: 10.1109/BROADNETS.2004.30
Murat Demirbas1, Anish Arora1, Vineet Mittal1, Vinod Kulathumani1
  • 1: Department of Computer Science and Engineering,The Ohio State University, Columbus, Ohio 43210 USA

Abstract

We present a fast local clustering service, FLOC, that partitions a multi-hop wireless network into nonoverlapping and approximately equal-sited clusters. Each cluster has a clusterhead such that all nodes within unit distance of the clusterhead belong to the cluster but no node beyond distance m from the clusterhead belongs to the cluster. By asserting m ≥ 2, FLOC achieves locality: effects of cluster formation and faults/changes at any part of the network are contained within most m units. By taking unit distance to be the reliable communication radius and m to be the maximum communication radius, FLOC exploits the double-band nature of wireless radio-model and achieves clustering in constant time regardless of the network size. Through simulations and experiments with actual deployments, we analyze the tradeoffs between clustering time and the quality of clustering, and suggest suitable parameters for FLOC to achieve a fast completion time without compromising the quality of the resulting clustering.