首页> 外文会议>2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks >Maximum lifetime effective-sensing partial target-coverage in camera sensor networks
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Maximum lifetime effective-sensing partial target-coverage in camera sensor networks

机译:相机传感器网络中最大使用寿命的有效感测部分目标覆盖率

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摘要

Due to the emerging multimedia applications, camera sensor network is getting more spotlight these days. The visual sensors adopted to implement camera sensor network are a kind of directional sensors, which are well-investigated in the context of directional sensor network in the literature. However, the design and implementation of camera sensor network pose additional challenges due to unique properties of visual sensors. In this paper, we consider an interesting sleep-wakeup scheduling problem in camera sensor network, namely the maximum lifetime effective-sensing partial target-coverage (ML-EPT) problem. Given a set of targets and a set of camera sensors with non-uniform remaining energy-level, the goal of ML-EPT is to compute a schedule of the camera sensors such that the continuous time duration, during which a partial coverage-level requirement over the targets is met, is maximized. We propose a new heuristic algorithm, namely the MEASURE-and-SLICE (MaS) algorithm, which are based on two sub procedures, MEASURE and SLICE. Our simulation result shows that MaS dominates its existing alternative on average, and is close to optimal in some restricted cases.
机译:由于新兴的多媒体应用,近来相机传感器网络越来越受到关注。用于实现相机传感器网络的视觉传感器是一种方向传感器,在文献中对方向传感器网络进行了深入研究。然而,由于视觉传感器的独特特性,相机传感器网络的设计和实现带来了额外的挑战。在本文中,我们考虑了相机传感器网络中一个有趣的睡眠-唤醒调度问题,即最大寿命有效感知部分目标覆盖(ML-EPT)问题。给定一组目标和一组具有不均匀剩余能量水平的摄像头传感器,ML-EPT的目标是计算摄像头传感器的计划,以使连续时间持续,在此期间需要部分覆盖水平超过目标,被最大化。我们提出了一种新的启发式算法,即MEASURE-and-SLICE(MaS)算法,该算法基于两个子过程MEASURE和SLICE。我们的仿真结果表明,MaS平均占主导地位,在某些受限情况下接近最优。

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