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Quantum Genetic Energy Efficient Iteration Clustering Routing Algorithm for Wireless Sensor Networks

Jianpo Li and Junyuan Huo
School of Information Engineering, Northeast Dianli University, Jilin, China
Abstract—Hierarchical routing algorithm as an energy optimization strategy has been widely considered as one of the effective ways to save energy for wireless sensor networks. In this paper, we propose a quantum genetic energy efficient iteration clustering routing algorithm (QGEEIC) for wireless sensor networks. To select the optimum cluster heads, the algorithm takes into account the balance of energy consumption by proposing an cluster selection method based on energy efficient iteration. At the same time, the clustering parameters are optimized by quantum genetic algorithm based on double-chain encoding method. In order to improve the adaptability to cluster structure of wireless sensor networks, the rotation angle and fitness function of quantum gate have been improved. Besides, we propose a solution to increase the number of initial individual in evolution. The simulation results show the superiority in terms of network lifetime, the number of alive nodes, and the total energy consumption.

Index Terms—Wireless sensor networks, energy optimization strategy, quantum genetic algorithm, iteration routing algorithm, routing algorithm

Cite: Jianpo Li and Junyuan Huo, "Quantum Genetic Energy Efficient Iteration Clustering Routing Algorithm for Wireless Sensor Networks," Journal of Communications, vol. 11, no. 12, pp. 1048-1056, 2016. Doi: 10.12720/jcm.11.12.1048-1056
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