Email this article A Novel Cluster-head Selection Algorithm Based on Hybrid Genetic Optimization for Wireless Sensor Networks
Abstract
Wireless Sensor Networks (WSN) represent a new dimension in the field of network research. The cluster algorithm can significantly reduce the energy consumption of wireless sensor networks and prolong the network lifetime. This paper uses neuron to describe the WSN node and constructs neural network model for WSN. The neural network model includes three aspects: WSN node neuron model, WSN node control model and WSN node connection model. Through learning the framework of cluster algorithm for wireless sensor networks, this paper presents a weighted average of cluster-head selection algorithm based on an improved Genetic Optimization which makes the node weights directly related to the decision-making predictions. The Algorithm consists of two stages: single-parent evolution and population evolution. The initial population is formed in the stage of single-parent evolution by using gene pool, then the algorithm continues to the next further evolution process, finally the best solution will be generated and saved in the population. The simulation results illustrate that the new algorithm has the high convergence speed and good global searching capacity. It is to effectively balance the network energy consumption, improve the network life-cycle, ensure the communication quality and provide a certain theoretical foundation for the applications of the neural networks.
Keywords
References
[1] YOUNISM A, “An Energy-aware QoS Routing Protocol for　Wireless Sensor Networks.” Proceedings of the 23rd International Conference on Distributed Computing Systems Workshops, Los Alamitos, USA: IEEE Computer Society, 2003, pp.710-715.
[2] PerrigA,SzewczykR,WenV, “SPINS: security protocols for sensor networks”, Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, USA: ACM, 2001,pp. 189~199.
[3] Heinemann W R, Chandrakasan A, Balakrishnan H, “An application-specific protocol architecture for wireless micro sensor networks”, IEEE Transaction on Wireless Communications, 2002, 1(4): 660~670.
[4] B. Liu and D. Towsley, “A Study on the Coverage of Large-Scale Sensor Networks,” Proc. First IEEE Int’l Conf. Mobile Ad-hoc and Sensor Systems (MASS ’04), pp. 475-483, Oct. 2004.
[5] Zhu Xiaorong, Shen Lianfeng, “RBF-based cluster-head selection for wireless sensor networks”, Journal of Southeast University (English Edition), 2006, 22 (4): 451-455.
[6] Ulakov A, Davcev D, “Data Mining in Wireless Sensor Networks Based on Artificial Neural Networks Algorithms,” Proc of the 1stInternational Workshop on Data Mining in Sensor Networks of SDM,USA: SIAM Press, 2005,pp. 10-16.
[7] Y.Liu, H.Ngan and L.M.Ni, “Power-Aware Node Deployment in Wireless Sensor Networks”, Int’l J. Distributed Sensor Networks, vol.3, pp. 225-241, April. 2007.
[8] Xiaorong Zhu, Lianfeng Shen, and Tak-Shing Peter Yum, “Hausdorff Clustering and Minimum Energy Routing for Wireless Sensor Networks”, IEEE Transactions on Vehicular Technology. Vol58, pp. 990 – 997, February. 2009.
[9] L. Xing, A. Shrestha, “QoS reliability of hierarchical clustered wireless sensor networks", IEEE International Conference on Performance, Computing, and Communications, 2006, pp. 641-646.
doi:10.1109/.2006.1629464
[10] T. Zhong, S.Wang, S. Z. Xu,H. F. Yu, D. Xu, “Time Delay Based Clustering in Wireless Sensor Networks", Wireless Communications and Networking Conference,2007, pp.3956-3960.
doi:10.1109/WCNC.2007.723
[11] Lejiang Guo, Qiang Tang, “An Improved Routing Protocol in WSN with Hybrid Genetic Algorithm”, The 2nd International Conference on Networks Security, Wireless Communications and Trusted Computing,2010, pp. 289-292.
[12] Sadjadi BA, Kiayias A, Mercado A, Yener B, “Robust key generation from signal envelopes in wireless networks.”, Proceedings of the 14th ACM Conference on Computer and Communications Security, 2007,pp.401-410.
doi:10.1145/1315245.1315295
[13] Wang Dong, Zhang Jin-rong, Cao Chang-xiu, “The estimating calculation and distributing regularity of wireless sensors”, Proceedings of the International Conference on Mechanical Transmissions. Chongqing, China: Science Press, 2006, pp. 532-1535.
[14] Lejiang Guo, Bingwen Wang, Weijiang Wang, “Research of energy-efficiency algorithm based on on-demand load balancing for wireless sensor networks”,2009 International Conference on Test and Measurement, 2009, pp. 22-25.
[15] Akyildiz F, Su W, Sankara subramaniam Y, Cayirci E, “A surveyon sensor networks”, IEEE Communications Magazine, 2002,pp.102–114.
doi:10.1109/MCOM.2002.1024422
[16] S. Lin, J. Zhang, G. Zhou, L. Gu, T. He, J.A. Stankovic, “ATPC: adaptive transmission power control for wireless sensor networks”, Proceedings of the International Conference on Embedded Networked Sensor Systems, November 2006, pp. 223-236.
doi:10.1145/1182807.1182830
[17] Kannan AA, Mao G, Vucetic B, “Simulated annealing based wireless sensor network localization”, Journal of Computers, 2006, 1(2): 15-22.
Full Text: PDF