摘要
针对传统的WSN覆盖模型的弊端,尤其是如果一个传感器失效,K-覆盖模型需要至少k个传感器节点监测其范围内是否有目标需要覆盖,提出了一种基于改进自适应遗传算法的移动WSN覆盖方法。在能量资源有限的前提下,尽可能长时间地对指定的目标进行连续监测。该算法考虑移动传感器是可以连续和变速运动的,从而能够保证所有目标都在它们的覆盖范围内。仿真结果表明,在使用移动节点的情况下,与其他常用模型相比,改进方法的生存周期和数据包数量都有明显提高。
Aiming at the drawbacks of the classical WSN coverage model,especially if a sensor dies, K -coverage model requires at least k sensor nodes to monitor whether there is a target within its coverage area,this paper proposed a mobile WSN coverage method based on improved adaptive genetic algorithm,which provided continuous monitoring of specified targets for longest possible time with limited energy resources.The algorithm took into account that the motion sensor could move at variable speeds continuously to ensure that all targets were within their coverage.Simulation results show that in the case of mobile nodes,the life span and the number of data packets of the improved method are obviously improved compared with other commonly models.
作者
朱利民
赵丽
Zhu Limin;Zhao Li(Dept. of Computer Science & Technology, Henan Institute of Technology, Xinxiang Henan 453000, China;School of Software, Shanxi University, Taiyuan 030013, China)
出处
《计算机应用研究》
CSCD
北大核心
2019年第5期1510-1514,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(61762086)
河南省科技厅科技攻关项目(162102310606)
河南省教育厅资助项目(16A520067)
关键词
无线传感器网络
自适应
改进遗传算法
K-覆盖
移动节点
wireless sensor networks(WSN)
adaptation
improved genetic algorithm
K-coverage
mobile node
