An energy-efficient K-hop clustering framework for wireless sensor networks

Quanbin CHEN*, Jian MA, Yanmin ZHU, Dian ZHANG, Lionel M. NI

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

11 Citations (Scopus)


Many applications in wireless sensor networks (WSNs) benefit significantly from organizing nodes into groups, called clusters, because data aggregation and data filtering applied in each cluster can greatly help to reduce traffic. The size of a cluster is measured by the hop distance from the farthest node to the cluster head. Rather than 1-hop clustering, K-hop clustering is preferred by many energy-constrained applications. However, existing solutions fail to distribute clusters evenly across the sensing field, which may lead to unbalanced energy consumption and network inefficiency. Moreover, they incur high communication overhead. We propose an Evenly Distributed Clustering (EDC) algorithm. Constrained by the maximum cluster size K, EDC distributes clusters uniformly, and minimizes the number of clusters. By introducing a relative synchronization technique, EDC converges fast with low communication overhead. It also helps to improve the successful transmission rate from nodes to their cluster heads. The simulation results indicate that EDC outperforms other existing algorithms.

Original languageEnglish
Title of host publicationWireless Sensor Networks : 4th European Conference, EWSN 2007, Delft, The Netherlands, January 29-31, 2007 : proceedings
EditorsKoen LANGENDOEN , Thiemo VOIGT
Place of PublicationBerlin
Number of pages17
ISBN (Electronic)9783540698302
ISBN (Print)9783540698296
Publication statusPublished - 2007
Externally publishedYes
Event4th European Conference on Wireless Sensor Networks, EWSN 2007 - Delft, Netherlands
Duration: 29 Jan 200731 Jan 2007

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume4373 LNCS
ISSN (Print)0302-9743


Conference4th European Conference on Wireless Sensor Networks, EWSN 2007


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