A Learning Based Method for Topology Control in Wireless Sensor Networks

S. H. Khasteh, S. Shouraki
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引用次数: 2

Abstract

Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption and radio interference, The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this paper we present a new distributed learning based method to choose nodes transmitting range, in this method we run a range adjustment mechanism periodically to choose a near optimal transmitting range, we don't need any information about location of nodes or distance between nodes or received signal strength, the communication overhead of this method is very low, performance evaluation results show that this method decrease the energy consumption and overcome other existing methods in some scenarios.
基于学习的无线传感器网络拓扑控制方法
拓扑控制(TC)是无线自组织和传感器网络中用于减少能量消耗和无线电干扰的最重要技术之一,该技术的目标是控制表示网络节点之间通信链路的图的拓扑结构,以保持某些全局图属性(例如连通性),同时减少与节点发射距离严格相关的能量消耗和/或干扰。本文提出了一种基于分布式学习的节点发射距离选择方法,该方法通过周期性运行距离调整机制来选择接近最优的发射距离,不需要任何节点位置、节点间距离和接收信号强度的信息,该方法的通信开销很低。性能评估结果表明,在某些场景下,该方法降低了能耗,克服了现有方法的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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