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A Cascaded Approach to Optimize Aircraft Trajectories for Persistent Data Ferrying

机译:级联方法优化飞机航迹的持久数据摆渡

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Unmanned aircraft are ideal vehicles for collecting and transferring data for sparse sensor networks, acting as data ferries for the networks. This paper investigates the optimality of periodic trajectories of an unmanned aircraft ferrying data between two stationary sensor nodes. The aircraft has a single half-duplex radio channel for wireless communication, and must allocate the channel along its trajectory to maximize data transfer between the nodes. The general data ferrying problem is known to be NP-Hard. This work takes advantage of the problem structure to cascade the solution between trajectory optimization and bandwidth optimization. We prove that this decomposition retains optimality, and further derive necessary conditions for trajectories to be optimal. In particular, the ferry must deliver exactly as much data as it collects over the periodic trajectory. Insights from these conditions lead to well-defined policies on bandwidth allocation. Our cascaded approach thus significantly reduces dimension of the persistent data ferrying problem.
机译:无人飞机是用于稀疏传感器网络收集和传输数据的理想工具,可充当网络的数据轮渡。本文研究了无人飞机在两个固定传感器节点之间运送数据的周期性轨迹的最优性。该飞机具有用于无线通信的单个半双工无线电信道,并且必须沿其轨迹分配该信道,以最大程度地增加节点之间的数据传输。已知的一般数据传送问题是NP-Hard。这项工作利用问题结构在轨迹优化和带宽优化之间级联解决方案。我们证明了这种分解保留了最优性,并进一步推导了使轨迹最优的必要条件。特别是,渡轮必须传递与在周期性轨迹上收集的数据一样多的数据。从这些条件中得出的见解导致制定了明确的带宽分配策略。因此,我们的级联方法显着减少了持久数据传送问题的规模。

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