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Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line

机译:优化用于最大化移动传感器寿命的运动,用于覆盖线上的目标

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Given a set of sensors distributed on the plane and a set of Point of Interests (POIs) on a line segment, a primary task of the mobile wireless sensor network is to schedule covering the POIs by the sensors, such that each POI is monitored by at least one sensor. For balancing the energy consumption, we study the min-max line barrier target coverage (LBTC) problem which aims to minimize the maximum movement of the sensors from their original positions to their final positions at which the coverage is composed. We first proved that when the radius of the sensors are non-uniform integers, even 1-dimensional LBTC (1D-LBTC), a special case of LBTC in which the sensors are distributed on the line segment instead of the plane, is NP-hard. The hardness result is interesting, since the continuous version of LBTC to cover a given line segment instead of the POIs is known polynomial solvable. Then we present an exact algorithm for LBTC with uniform radius and sensors distributed on the plane, via solving the decision version of LBTC. We argue that our algorithm runs in time O(n2logn) and produces an optimal solution to LBTC. The time complexity compares favorably to the state-of-art runtime O(n3logn) of the continuous version which aims to cover a line barrier instead of the targets. Last but not the least, we carry out numerical experiments to evaluate the practical performance of the algorithms, which demonstrates a practical runtime gain comparing with an optimal algorithm based on integer linear programming.
机译:给定一组分布在所述平面传感器与上一个线段的一组兴趣点(POI)的路线时,移动无线传感器网络的主要任务是调度由传感器,使得每个POI被监视覆盖所述POI的至少一个传感器。为了平衡能耗,我们研究了最小 - 最大线路不通目标覆盖(LBTC)的问题,其目的是从原来的位置,以它们的最终位置,在该范围由最小化传感器的最大动作。我们首先证明,当传感器的半径是不均匀的整数,甚至1维LBTC(1D-LBTC),LBTC的一种特殊情况,其中,传感器被分布在线段而不是平面,是NP-难的。硬度结果是有趣的,因为LBTC的连续版本,以覆盖给定的线段代替的POI是已知的多项式可解的。然后,我们提出了LBTC均匀半径和分布在飞机上的传感器的精确算法,通过求解LBTC的判决版本。我们认为,我们的算法在运行时间O(n2logn),并产生一个最佳的解决方案,以LBTC。的时间复杂度相比毫不逊色的状态的最先进的运行时间为O(n3logn)的连续版本旨在覆盖线屏障,而不是目标的哪个。最后但并非最不重要的,我们进行数值试验,以评估该算法的实用性能,这表明实际运行时的增益与基于整数线性规划的优化算法进行比较。

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