期刊
JOURNAL OF SYSTEMS AND SOFTWARE
卷 146, 期 -, 页码 196-214出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jss.2018.09.067
关键词
Wireless sensor networks; Clustering algorithm; Genetic algorithm; Energy-efficiency; Network life cycle; Routing
Wireless sensor networks have been employed widely in various fields, including military, health care, and manufacturing applications. However, the sensor nodes are limited in terms of their energy supply, storage capability, and computational power. Thus, in order to improve the energy efficiency and prolong the network life cycle, we present a genetic algorithm-based energy-efficient clustering and routing approach GECR. We add the optimal solution obtained in the previous network round to the initial population for the current round, thereby improving the search efficiency. In addition, the clustering and routing scheme are combined into a single chromosome to calculate the total energy consumption. We construct the fitness function directly based on the total energy consumption thereby improving the energy efficiency. Moreover, load balancing is considered when constructing the fitness function. Thus, the energy consumption among the nodes can be balanced. The experimental results demonstrated that the GECR performed better than other five methods. The GECR achieved the best load balancing with the lowest variances in the loads on the cluster heads under different scenarios. In addition, the GECR was the most energy-efficient with the lowest average energy consumed by the cluster heads and the lowest energy consumed by all the nodes. (C) 2018 Elsevier Inc. All rights reserved.
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