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Energy efficient clustering algorithm based on neighbors for wireless sensor networks 被引量:1

Energy efficient clustering algorithm based on neighbors for wireless sensor networks
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摘要 In this paper, an energy efficient clustering algorithm based on neighbors (EECABN) for wireless sensor networks is proposed. In the algorithm, an optimized weight of nodes is introduced to determine the priority of clustering procedure. As improvement, the weight is a measurement of energy and degree as usual, and even associates with distance from neighbors, distance to the sink node, and other factors. To prevent the low energy nodes being exhausted with energy, the strong nodes should have more opportunities to act as cluster heads during the clustering procedure. The simulation results show that the algorithm can effectively prolong whole the network lifetime. Especially at the early stage that some nodes in the network begin to die, the process can be postponed by using the algorithm. In this paper, an energy efficient clustering algorithm based on neighbors (EECABN) for wireless sensor networks is proposed. In the algorithm, an optimized weight of nodes is introduced to determine the priority of clustering procedure. As improvement, the weight is a measurement of energy and degree as usual, and even associates with distance from neighbors, distance to the sink node, and other factors. To prevent the low energy nodes being exhausted with energy, the strong nodes should have more opportunities to act as cluster heads during the clustering procedure. The simulation results show that the algorithm can effectively prolong whole the network lifetime. Especially at the early stage that some nodes in the network begin to die, the process can be postponed by using the algorithm.
作者 周伟
出处 《Journal of Shanghai University(English Edition)》 CAS 2011年第2期150-153,共4页 上海大学学报(英文版)
基金 Project supported by the Shanghai Leading Academic Discipline Project (Grant No.S30108)
关键词 wireless sensor networks CLUSTERING WEIGHT network lifetime wireless sensor networks, clustering, weight, network lifetime
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