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A learning automata-based algorithm for solving coverage problem in directional sensor networks

机译：基于学习自动机的定向传感器网络覆盖问题求解算法

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摘要

Wireless sensor networks have been used in a wide variety of applications. Recently, networks consisting of directional sensors have gained prominence. An important challenge facing directional sensor networks (DSNs) is maximizing the network lifetime while covering all the targets in an area. One effective method for saving the sensors' energy and extending the network lifetime is to partition the DSN into several covers, each of which can cover all targets, and then to activate these covers successively. This paper first proposes a fully distributed algorithm based on irregular cellular learning automata to find a near-optimal solution for selecting each sensor's appropriate working direction. Then, to find a near-optimal solution that can cover all targets with the minimum number of active sensors, a centralized approximation algorithm is proposed based on distributed learning automata. This algorithm takes advantage of learning automata (LA) to determine the sensors that must be activated at each stage. As the presented algorithm proceeds, the activation process is focused on the sensor nodes that constitute the cover set with the minimum number of active sensors. Through simulations, we indicate that the scheduling algorithm based on LA has better performance than the greedy algorithm-based scheme in terms of maximizing network lifetime.
机译：无线传感器网络已被广泛应用。近来，由方向传感器组成的网络日益受到关注。定向传感器网络（DSN）面临的一个重要挑战是最大化网络寿命，同时覆盖区域中的所有目标。节省传感器能量和延长网络寿命的一种有效方法是将DSN分成几个覆盖物，每个覆盖物可以覆盖所有目标，然后依次激活这些覆盖物。本文首先提出了一种基于不规则细胞学习自动机的全分布式算法，以找到用于选择每个传感器的合适工作方向的最佳方案。然后，为了找到可以用最少数量的有源传感器覆盖所有目标的接近最优的解决方案，提出了一种基于分布式学习自动机的集中式近似算法。该算法利用学习自动机（LA）来确定必须在每个阶段激活的传感器。随着提出的算法的进行，激活过程集中在传感器节点上，这些传感器节点构成具有最少数量的活动传感器的封面集。通过仿真表明，在最大化网络寿命方面，基于LA的调度算法比基于贪婪算法的调度算法具有更好的性能。

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  • 来源
    《Computing》 |2013年第1期|1-24|共24页
  • 作者

    Hosein Mohamadi; Abdul Samad Bin Haji Ismail; Shaharuddin Salleh;

  • 作者单位

    Computer Department, Faculty of Computer Science and Information, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia;

    Computer Department, Faculty of Computer Science and Information, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia;

    Mathematics Department, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    directional sensor networks; cover set formation; distributed learning automata;

    机译：定向传感器网络;封面集形成;分布式学习自动机;

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