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An adaptive path planning algorithm for mobile-anchor based wireless sensor networks

机译:基于移动锚的无线传感器网络的自适应路径规划算法

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In wireless sensor networks, anchor positions play an important role for high localization accuracy. Planning an efficient path for mobile anchor nodes (MN) is critical for required anchor positions. In this work, an adaptive path planning algorithm is proposed for mobile anchors based on Gauss-Markov mobility model. The approach, which the velocity adjustment, the perpendicular bisector and the virtual repulsive strategies are combined based on Gauss-Markov mobility, is improved by developing a grid based virtual repulsive force strategy. To enhance the localization accuracy, the surveillance area is divided into grids and the grid based virtual repulsive force is applied to the MN if it is located in an anchor dense area. The simulation results show that defining a grid based virtual repulsive strategy increase the localization accuracy and cover more surveillance region using less energy.
机译:在无线传感器网络中,锚点位置对于高定位精度起着重要作用。规划移动锚节点(MN)的有效路径对于所需的锚位置至关重要。在这项工作中,提出了一种基于高斯-马尔可夫移动性模型的移动锚点自适应路径规划算法。通过开发基于网格的虚拟排斥力策略,改进了将速度调整,垂直平分线和虚拟排斥策略相结合的方法。为了提高定位精度,将监视区域划分为网格,并且如果基于网格的虚拟排斥力位于MN的锚点密集区域,则将其应用于MN。仿真结果表明,定义基于网格的虚拟排斥策略可提高定位精度,并使用更少的能量覆盖更多的监视区域。

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