TY - GEN
T1 - An energy-efficient K-hop clustering framework for wireless sensor networks
AU - CHEN, Quanbin
AU - MA, Jian
AU - ZHU, Yanmin
AU - ZHANG, Dian
AU - NI, Lionel M.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=38049110063&partnerID=8YFLogxK
UR - https://www.researchgate.net/publication/221420364_An_Energy-Efficient_K-Hop_Clustering_Framework_for_Wireless_Sensor_Networks
U2 - 10.1007/978-3-540-69830-2_2
DO - 10.1007/978-3-540-69830-2_2
M3 - Conference paper (refereed)
AN - SCOPUS:38049110063
SN - 9783540698296
T3 - Lecture Notes in Computer Science
SP - 17
EP - 33
BT - Wireless Sensor Networks : 4th European Conference, EWSN 2007, Delft, The Netherlands, January 29-31, 2007 : proceedings
A2 - LANGENDOEN , Koen
A2 - VOIGT, Thiemo
PB - Springer
CY - Berlin
T2 - 4th European Conference on Wireless Sensor Networks, EWSN 2007
Y2 - 29 January 2007 through 31 January 2007
ER -