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A Hybrid Energy- and Time-Driven Cluster Head Rotation Strategy for Distributed Wireless Sensor Networks
Author(s) -
MA Guo-xi,
Zhengsu Tao
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/109307
Subject(s) - computer science , rotation (mathematics) , energy (signal processing) , wireless sensor network , cluster (spacecraft) , efficient energy use , energy consumption , cluster analysis , real time computing , computer network , artificial intelligence , electrical engineering , engineering , statistics , mathematics
Clustering provides an effective way to extend the lifetime and improve the energy efficiency of wireless sensor networks (WSNs). However, the cluster heads will deplete energy faster than cluster members due to the additional tasks of information collection and transmission. The cluster head rotation among sensors is adopted to solve this problem. Cluster head rotation strategies can be generally divided into two categories: time-driven strategy and energy-driven strategy. The time-driven strategy can balance energy consumption better, but it is not suitable for heterogonous WSNs. The energy-driven cluster head rotation strategy has high energy efficiency, especially in heterogonous networks. However, the rotation will become increasingly frequent with the reduction of the nodes residual energy for this strategy, which causes lots of energy waste. In this paper, we propose a hybrid cluster head rotation strategy which combines the advantages of both energy-driven and time-driven cluster head rotation strategies. In our hybrid rotation strategy, the time-driven strategy or energy-driven strategy will be selected according to the residual energy. Simulations show that the hybrid strategy can enhance the energy efficiency and prolong network lifetime in both homogeneous and heterogeneous networks, compared with either single time-driven or energy-driven cluster head rotation method. © 2013 Guoxi Ma and Zhengsu Tao.

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