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Minimizing effective energy consumption in multi-cluster sensor networks for source extraction

机译:最小化多群集传感器网络中用于源提取的有效能耗

摘要

This paper studies a multi-cluster sensor network which is applied for source extraction in a sensing field. Both the performance of source extraction and the total energy consumption in the sensor network are functions of the number of clusters. In this paper, we aim at finding the optimal number of clusters by minimizing the effective energy consumption which is defined as the ratio of the performance of source extraction to the total energy consumption in the sensor network. A particle swarm optimization (PSO) algorithm is employed to form the clusters which enables every cluster to perform source extraction. The existence and the uniqueness of the optimum number of clusters is proven theoretically and shown by numerical simulations. The relationship between the optimum number of clusters and the various system parameters are investigated. A tradeoff between the performance and the total energy consumption is illustrated. The results show that the performance is greatly improved by adopting the multi-cluster structure of the sensor network.
机译:本文研究了一种多群集传感器网络,该网络用于传感领域中的源提取。源提取的性能和传感器网络中的总能耗都取决于群集数量。在本文中,我们旨在通过最小化有效能耗来找到最佳的簇数,有效能耗定义为传感器网络中源提取性能与总能耗之比。粒子群优化(PSO)算法用于形成集群,使每个集群都能执行源提取。理论上证明了最优簇数的存在和唯一性,并通过数值模拟表明了这一点。研究了最佳簇数与各种系统参数之间的关系。说明了性能与总能耗之间的折衷。结果表明,采用传感器网络的多簇结构可以大大提高性能。

著录项

  • 作者

    Chen H; Tse CK; Feng J;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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