For the large-scale monitoring of a physical phenomena using a wireless sensor network (WSN), a large number of static and/or mobile sensor nodes are required, resulting in higher deployment cost. In this work, we develop an efficient algorithm that can employ a small number of static nodes together with a set of mobile nodes for improved area coverage. An efficient deployment of static nodes and guided mobility of the mobile nodes is critical for maximizing the area coverage. To this end, we propose three mixed integer linear programming (MILP) formulations. The first formulation efficiently deploys a set of static nodes and the other two formulations plan the path of a set of mobile nodes so as to maximize the area coverage and minimize the total number of movements required to achieve the desired coverage. We present extensive performance evaluation of the proposed algorithms and its comparison with benchmark approaches. The simulation results demonstrate the superior performance of the proposed algorithms for different network sizes and number of static and mobile nodes.

翻译：针对利用无线传感器网络（WSN）进行大规模物理现象监测时所需大量静态和/或移动传感器节点导致部署成本较高的问题，本文提出一种高效算法，通过部署少量静态节点与一组移动节点协同提升区域覆盖性能。静态节点的优化部署与移动节点的受控移动对于最大化区域覆盖至关重要。为此，我们提出三种混合整数线性规划（MILP）模型：第一种模型高效部署静态节点集，另外两种模型规划移动节点路径，以最大化区域覆盖并最小化实现目标覆盖所需的总移动次数。我们对该算法进行了全面的性能评估，并与基准方法进行对比。仿真结果表明，所提算法在不同网络规模及静态/移动节点数量场景下均展现出优越性能。