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Prolonging Network Lifetime for Target Coverage in Sensor Networks

机译:延长网络寿命以覆盖传感器网络中的目标

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摘要

Target coverage is a fundamental problem in sensor networks for environment monitoring and surveillance purposes. To prolong the network lifetime, a typical approach is to partition the sensors in a network for target monitoring into several disjoint subsets such that each subset can cover all the targets. Thus, each time only the sensors in one of such subsets are activated. It recently has been shown that the network lifetime can be further extended through the overlapping among these subsets. Unlike most of the existing work in which either the subsets were disjoint or the sensors in a subset were disconnected, in this paper we consider both target coverage and sensor connectivity by partitioning an entire lifetime of a sensor into several equal intervals and allowing the sensor to be contained by several subsets to maximize the network lifetime. We first analyze the energy consumption of sensors in a Steiner tree rooted at the base station and spanning the sensors in a subset. We then propose a novel heuristic algorithm for the target coverage problem, which takes into account both residual energy and coverage ability of sensors. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithm by varying the number of intervals of sensor lifetime and network connectivity. The experimental results show that the network lifetime delivered by the proposed algorithm is further prolonged with the increase of the number of intervals and improvement of network connectivity.
机译:目标覆盖是传感器网络中用于环境监视和监视目的的基本问题。为了延长网络寿命,一种典型的方法是将网络中用于目标监视的传感器划分为几个不相交的子集,以便每个子集可以覆盖所有目标。因此,每次仅激活此类子集中的一个子集中的传感器。最近已经表明,通过这些子集之间的重叠可以进一步延长网络寿命。与大多数现有工作中子集不相交或子集中的传感器断开连接不同,在本文中,我们通过将传感器的整个生命周期划分为几个相等的间隔并允许传感器进行分离,来考虑目标覆盖率和传感器的连通性。由几个子集包含以最大化网络寿命。我们首先分析植根于基站的Steiner树中传感器的能耗,并在子集中跨越传感器。然后,我们针对目标覆盖问题提出了一种新颖的启发式算法,该算法同时考虑了剩余能量和传感器的覆盖能力。我们最终通过仿真进行实验,以通过更改传感器寿命和网络连接的间隔数来评估所提出算法的性能。实验结果表明,随着时间间隔的增加和网络连通性的提高,该算法的网络寿命进一步延长。

著录项

  • 来源
  • 会议地点 DallasTX(US);DallasTX(US)
  • 作者

    Yuzhen Liu; Weifa Liang;

  • 作者单位

    Department of Computer Science, The Australian National University Canberra, ACT 0200, Australia;

    Department of Computer Science, The Australian National University Canberra, ACT 0200, Australia;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机网络;
  • 关键词

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