HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks

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HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks (2004)

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by Ossama Younis , Sonia Fahmy

Venue:	IEEE TRANS. MOBILE COMPUTING
Citations:	589 - 1 self

BibTeX

@ARTICLE{Younis04heed:a,
    author = {Ossama Younis and Sonia Fahmy},
    title = {HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks},
    journal = {IEEE TRANS. MOBILE COMPUTING},
    year = {2004},
    pages = {366--379}
}

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Abstract

Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. In this paper, we propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in Oð1Þ iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.

Keyphrases

ad hoc sensor network sensor node distributed clustering approach network lifetime network scalability effective topology control approach secondary parameter long-lived ad hoc sensor network guarantee connectivity node residual energy node capability appropriate bound hybrid energy-efficient distributed clustering node proximity fault tolerance scalable data aggregation incurs low message overhead multiple power level sensor network balance load node density cluster head intercluster transmission energy efficiency index term sensor network node degree abstract topology control simulation result uniform cluster head distribution clustered network

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