基于覆盖集和逆高斯变异的AFSA算法在WSN中的覆盖研究

Research on the Covering of AFSA in WSN Based on Covering Set and Inverse Gaussian Mutation

针对人工鱼群算法(AFSA)对节点能量以及分布考虑不足的情况,本文在无线传感优化覆盖中,引入了覆盖集和逆高斯变异概念,通过在AFSA的觅食阶段采用覆盖集,使得个体人工鱼的选择的效率得到提高,在聚群阶段使用逆高斯变异,将个体人工鱼的活动区域进行了合理的分布,使得探寻食物的效率得到了提供。通过经典函数测试,本文的算法在性能上优于AFSA算法,通过仿真实验证明,本文算法在节点能量消耗上和节点覆盖效率上有了进一步的提高。

In this paper, considering the situation that the node energy and distribution are not consideredsufficiently in the Artificial Fish Swarm Algorithm （AFSA）, the concepts of Covering Set and InverseGaussian Mutation are introduced to the wireless sensing optimized covering. By using the covering set atthe foraging phase of AFSA, the efficiency of the selection of individual artificial fish is improved. In theclustering stage, Inverse Gaussian Mutation is used to properly distribute the activity zone of individualartificial fish, making the efficiency of foraging improved. Through classical function test, the algorithmof this paper is better than AFSA. And through simulation experiment, it proves that the algorithm of thispaper is furthered improved in node energy consumption and node covering efficiency.