Energy-efficient routing for wireless sensor network using genetic algorithm and particle swarm optimisation techniques

被引：0
作者：
机构：
[1] Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Surat
[2] Department of Computer Engineering, Sardar Vallabhbhai National Institute of Technology, Surat
来源：
Rana, K. (keyur.rana@scet.ac.in) | 1600年 / Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland卷 / 06期
关键词：
A-star algorithm; Energy-efficient routing; Genetic algorithm; Particle swarm optimisation; Wireless sensor network;
D O I：
10.1504/IJWMC.2013.056548
中图分类号：
学科分类号：
摘要：
There are several techniques for routing in wireless sensor network (WSN). Using minimum transmission energy model and minimum hop routing model techniques it may happen that the same path is used for more times and nodes on this route are drained of energy. This leads to network partition and thus, reduction in network lifetime which makes the routing algorithm unsuccessful and ineffective. Energy conservation in the WSN is of paramount importance. In this paper, we present energy-efficient routing techniques for two-tiered WSN using Genetic Algorithm, Particle Swarm Optimisation and A-Star algorithm based approach to enhance lifetime of the network. Result analysis shows that A-star algorithm based approach extends lifetime of sensor network comparatively more. But after network lifetime is over, PSO and GA based approach preserves more stronger nodes which signifies that selection/rotation of cluster head strategy can improve performance of network. Copyright © 2013 Inderscience Enterprises Ltd.
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页码：392 / 406
页数：14
相关论文
共 24 条
  • [21] Rana K.M., Zaveri M.A., Genetic algorithm based routing technique to extend lifetime of wireless sensor network, International Journal of Advanced Research in Computer Science, 1, 2, pp. 126-132, (2010)
  • [22] Rana K.M., Zaveri M.A., A-Star algorithm for energy efficient routing in wireless sensor network, NeCoM/WeST/WiMoN 2011 Chennai, India July 2011, Communications in Computer and Information Science, 197, pp. 232-241, (2011)
  • [23] Trelea I.C., The particle swarm optimization algorithm: Convergence analysis and parameter selection, Information Processing Letters, 85, pp. 317-325, (2003)
  • [24] Villafuerte F.L., Schiller J., DIN: An ad-hoc algorithm to estimate distances in wireless sensor networks, Proceedings of the 7th International Conference on Ad-hoc, Mobile and Wireless Networks, 5198, pp. 162-175, (2008)
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