路径覆盖是无线传感器网络目标监控领域的一个热点研究问题,在分析节点主感知方向可调模型的基础上,提出了一种基于改进势场的有向传感器网络路径覆盖增强算法(improved potential field based path coverage-enhancing algorithm,IPFPC...路径覆盖是无线传感器网络目标监控领域的一个热点研究问题,在分析节点主感知方向可调模型的基础上,提出了一种基于改进势场的有向传感器网络路径覆盖增强算法(improved potential field based path coverage-enhancing algorithm,IPFPCA).该算法针对传统虚拟势场可能出现的局部极小导致覆盖增强失败问题设计了一种改进的势场函数,通过将相邻传感器节点对路径轨迹点的共同覆盖率引入到斥力计算中,有效引导节点的主感知方向调整,从而达到路径的高效覆盖.实验结果表明:对比已有的路径覆盖增强算法,IPFPCA可以消除节点的感知重叠区和盲区,最终实现网络路径的高效覆盖.展开更多
This paper proposes an adaptive localization approach for wireless sensor networks based on Gauss-Markov mobility model. In the approach,the perpendicular bisector strategy,the virtual repulsive strategy,and the veloc...This paper proposes an adaptive localization approach for wireless sensor networks based on Gauss-Markov mobility model. In the approach,the perpendicular bisector strategy,the virtual repulsive strategy,and the velocity adjustment strategy are properly combined to enhance localization effciency. The velocity adjustment strategy causes that the mobile anchor node automatically tunes its velocity. The perpendicular bisector strategy locally adjusts trajectory for the mobile anchor node,which ensures that unknown nodes obtain enough non-collinear anchor coordinates as soon as possible. The virtual repulsive strategy impels that the mobile anchor node rapidly leaves the communication range of location-aware nodes or returns to the surveillance region after the mobile anchor node was out of the boundary. Both theoretical analysis and simulation studies show that this approach can increase localization accuracy,consume less energy,and cover more surveillance region during the same period than virtual beacons-energy ratios localization scheme using the Gauss-Markov mobility model.展开更多
文摘路径覆盖是无线传感器网络目标监控领域的一个热点研究问题,在分析节点主感知方向可调模型的基础上,提出了一种基于改进势场的有向传感器网络路径覆盖增强算法(improved potential field based path coverage-enhancing algorithm,IPFPCA).该算法针对传统虚拟势场可能出现的局部极小导致覆盖增强失败问题设计了一种改进的势场函数,通过将相邻传感器节点对路径轨迹点的共同覆盖率引入到斥力计算中,有效引导节点的主感知方向调整,从而达到路径的高效覆盖.实验结果表明:对比已有的路径覆盖增强算法,IPFPCA可以消除节点的感知重叠区和盲区,最终实现网络路径的高效覆盖.
基金Supported by National Natural Science Foundation of China(60776834, 60870010)
文摘This paper proposes an adaptive localization approach for wireless sensor networks based on Gauss-Markov mobility model. In the approach,the perpendicular bisector strategy,the virtual repulsive strategy,and the velocity adjustment strategy are properly combined to enhance localization effciency. The velocity adjustment strategy causes that the mobile anchor node automatically tunes its velocity. The perpendicular bisector strategy locally adjusts trajectory for the mobile anchor node,which ensures that unknown nodes obtain enough non-collinear anchor coordinates as soon as possible. The virtual repulsive strategy impels that the mobile anchor node rapidly leaves the communication range of location-aware nodes or returns to the surveillance region after the mobile anchor node was out of the boundary. Both theoretical analysis and simulation studies show that this approach can increase localization accuracy,consume less energy,and cover more surveillance region during the same period than virtual beacons-energy ratios localization scheme using the Gauss-Markov mobility model.
