Journal
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
Volume 14, Issue 1, Pages 76-84Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2015.2446475
Keywords
Fuzzy clustering; particle swarm optimization; cluster head selection; wireless sensor network
Categories
Funding
- Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou, China [KJS1223]
- National Natural Science Foundation of China [61170164]
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An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.
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