Cluster algorithm of Wireless Sensor Networks Based on Immune Clonal Selection
In light of the traditional Wireless Sensor Network clustering algorithms are lack of adaptive capacity, in this paper, we propose a clustering algorithm based on Immune Clone Selection Principle (ICSA), make use of global search ability and faster rate characteristics of ICSA, in accordance with the Wireless Sensor Network nodes in the distribution of the actual situation of WSN network, the simulation results show that the algorithm is able to cluster the network reasonable and effective to extend the network life, compared to the traditional clustering algorithm LEACH, the clustering algorithm based on ICSA has a better Performance. Standard clone selection algorithm and to make improvements in the mutation operator into the thinking of simulated annealing, so that fast convergence algorithm can effectively search a global optimal solution. Simulation studies show that the node scheduling algorithm is correct, effective, and has a good energy saving effect.Compared to standard ICSA, its global searching ability and the speed of convergence is significantly improved, and the premature convergence problem is effectively avoided. In addition, according to the rationalization of cluster-head selection, this article introduces a cluster-head rotation mechanism, which is based on energy balance. Through simulation and comparison with other algorithms, it is obvious that this algorithm can effectively balance energy consumption and extend the lifetime of WSN.
Wireless Sensor Network Immune Clone Selection Algorithm clustering algorithm optimization
Lei Lin Zhao Ji Wang Houjun
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 610054
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
2006-2009
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）