A Probabilistic Barrier Coverage Model and Effective Construction Scheme
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摘要: K-栅栏覆盖是有向传感器网络的研究热点之一.概率感知模型要比0-1模型更贴近实际.而基于概率感知模型的栅栏覆盖还鲜有研究.根据感知概率阈值和感知距离要求，确定节点的虚拟半径.提出一种二元概率栅栏覆盖模型.在这个模型中，相邻2个节点的虚拟感知圆两两相切.在此基础上提出了最少节点的概率栅栏构建算法(construction of probabilistic barrier of minimum node, CPBMN).首先根据二元概率栅栏模型确定节点的目标位置，再通过匈牙利算法选用移动距离之和最少的移动节点移动到目标位置形成栅栏覆盖，缺少移动节点的子区域，选择附近区域的剩余移动节点修补形成1-栅栏覆盖.水平相邻的2个子区域之间构建竖直栅栏，这些子区域的概率1-栅栏合起来构成整个区域的概率K-栅栏覆盖.仿真结果证明：该方法能够有效形成概率栅栏，最多比其他栅栏构建算法节省70%能耗.Abstract: Barrier coverage is one of hot spots in the wireless sensor network. The probabilistic sensing model is closer to the actual situation than 0-1 sensing model. However, there is seldom study about probabilistic barrier coverage. This paper mainly studies virtual radius according to the probabilistic sensing model and the demand of detecting distance. And this paper also proposes the binary probabilistic barrier coverage model in which the neighbor virtual sensing circles are tangent. The CPBMN (construction of probabilistic barrier of minimum node) is also proposed based on this probabilistic barrier model. Firstly, the optimal target locations are determined by the binary probabilistic barrier coverage mode. Secondly, the Hungary algorithm selects the corresponding optimal mobile nodes to shift its target location. Thirdly, the vertical barriers between two horizontal adjacent probabilistic barrier segments are created. The K-probabilistic barriers in the whole area are created by combining these 1-probabilistic barriers in each subarea together. Simulation results show our method can effectively constitute probabilistic barrier coverage. Compared with other methods, it can decrease 70% energy consumption.
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