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Unmanned air vehicles (UAVs) can provide important communication advantages to ground-based wireless ad hoc networks. In this paper, the location and movement of UAVs are optimized to improve the connectivity of a wireless network. Four types of network connectivity are quantified: global message connectivity, worst-case connectivity, network bisection connectivity, and k -connectivity. The problems of UAV deployment and movement are formulated to improve the different types of connectivity. Both problems are NP -hard. For the deployment case, some heuristic adaptive schemes are proposed to yield simple but effective solutions. In addition, a closed-form solution for the two-node one-UAV case is provided. For k -connectivity, we propose an algorithm that improves connectivity using Delaunay triangulation. To optimize the UAV movement, an algorithm that tracks changes in the network topology is constructed. The simulation results show that by only deploying a single UAV, the global message network connectivity and the worst-case network connectivity can be improved by up to 109% and 60%, respectively. The network bisection connectivity and the k -connectivity can also be significantly improved.
Han et al. (Thu,) studied this question.