TY - GEN
T1 - An energy-efficient balanced clustering algorithm for wireless sensor networks
AU - Zhigao, Du
AU - Yi, Liu
AU - Depei, Qian
PY - 2009
Y1 - 2009
N2 - Clustering is a popular topology control method in wireless sensor networks, which can facilitate the network selfmanagement and make it easy to devise the communication protocols. Also clustering can improve energy efficiency and the network scalability. Existing clustering algorithms concern much about the local energy consumption, but little about the overall energy consumption. A novel energy-efficient, balanced clustering algorithm EEBC is proposed in this paper. In EEBC the sensor nodes are clustered randomly at first, and then they conduct self-adaptive optimization to balance the size of clusters. The structure of the cluster is fixed after the optimization. The operation of EEBC is divided into rounds. At the end of each round the current cluster head selects a node from its cluster members as the next cluster head. The process of the cluster head rotation is transparent to other cluster members. The results of simulations show that EEBC outperforms existing algorithms in energy efficiency and clustering balance.
AB - Clustering is a popular topology control method in wireless sensor networks, which can facilitate the network selfmanagement and make it easy to devise the communication protocols. Also clustering can improve energy efficiency and the network scalability. Existing clustering algorithms concern much about the local energy consumption, but little about the overall energy consumption. A novel energy-efficient, balanced clustering algorithm EEBC is proposed in this paper. In EEBC the sensor nodes are clustered randomly at first, and then they conduct self-adaptive optimization to balance the size of clusters. The structure of the cluster is fixed after the optimization. The operation of EEBC is divided into rounds. At the end of each round the current cluster head selects a node from its cluster members as the next cluster head. The process of the cluster head rotation is transparent to other cluster members. The results of simulations show that EEBC outperforms existing algorithms in energy efficiency and clustering balance.
KW - Balanced clustering
KW - Cluster head rotation
KW - Energy-efficient
KW - Self-adaptive iteration
KW - Wireless sensor networks
UR - https://www.scopus.com/pages/publications/73149107999
U2 - 10.1109/WICOM.2009.5302942
DO - 10.1109/WICOM.2009.5302942
M3 - 会议稿件
AN - SCOPUS:73149107999
SN - 9781424436934
T3 - Proceedings - 5th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2009
BT - Proceedings - 5th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2009
T2 - 5th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2009
Y2 - 24 September 2009 through 26 September 2009
ER -