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Weak Coverage of a Rectangular Barrier

机译:矩形屏障的弱覆盖

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摘要

Assume n wireless mobile sensors are initially dispersed in an ad hoc manner in a rectangular region. They are required to move to final locations so that they can detect any intruder crossing the region in a direction parallel to the sides of the rectangle, and thus provide weak barrier coverage of the region. We study three optimization problems related to the movement of sensors to achieve weak barrier coverage: minimizing the number of sensors moved (MinNum), minimizing the average distance moved by the sensors (MinSum), and minimizing the maximum distance moved by the sensors (MinMax). We give an O(n~(3/2)) time algorithm for the MinNum problem for sensors of diameter 1 that are initially placed at integer positions; in contrast we show that the problem is NP-hard even for sensors of diameter 2 that are initially placed at integer positions. We show that the MinSum problem is solvable in O(n log n) time for homogeneous range sensors in arbitrary initial positions for the Manhattan metric, while it is NP-hard for heterogeneous sensor ranges for both Manhattan and Euclidean metrics. Finally, we prove that even very restricted homogeneous versions of the MinMax problem are NP-hard.
机译:假设N无线移动传感器最初以矩形区域分散在矩形区域中。它们需要移动到最终位置,使得它们可以在平行于矩形侧面的方向上检测到区域的任何入侵者,从而提供该区域的弱势屏障覆盖。我们研究了与传感器的运动有关的三个优化问题,以实现弱势屏障覆盖:最小化移动的传感器数量(Minnum),最大限度地减少由传感器(Minsum)移动的平均距离,并最大限度地减少由传感器移动的最大距离(Minmax )。对于最初放置在整数位置的直径1的传感器,我们给出O(n〜(3/2))时间算法。相比之下,即使对于最初放置在整数位置的直径2的传感器,问题也是NP - 硬质的。我们表明,对于曼哈顿公制的任意初始位置的均匀初始位置的均匀范围传感器的o(n log n)时间是可解决的,而曼哈顿和欧几里德度量的异质传感器范围是Np-hard。最后,我们证明了甚至非常受限制的MinMax问题的均匀版本是NP - 硬。

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