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A game theory distributed approach for energy optimization in WSNs

Published: 23 July 2013 Publication History
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  • Abstract

    One of the major sources of energy waste in wireless sensor networks (WSNs) is idle listening, that is, the cost of actively listening for potential packets. This article focuses on reducing idle-listening time via a dynamic duty-cycling technique which aims at optimizing the sleep interval between consecutive wake-ups. We considered a receiver-initiated MAC method for WSNs in which the sender waits for a beacon signal from the receiver before starting to transmit. Since each sender receives beacon signals from several nodes, the data are routed on multiple paths in a data collection network. In this context, we propose an optimization framework for minimizing the energy waste of the most power-hungry node of the network. To this aim, we first derive an analytic model that predicts nodes' energy consumption. Then, we use the model to derive a distributed optimization technique. Simulation results via NS-2 simulator are included to illustrate the accuracy of the model, and numerical results assess the validity of the proposed scheme.

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      Published In

      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 9, Issue 4
      July 2013
      523 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/2489253
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 23 July 2013
      Accepted: 01 August 2012
      Revised: 01 April 2012
      Received: 01 September 2011
      Published in TOSN Volume 9, Issue 4

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      1. Wireless sensor networks

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      • (2023)A Density Routing Algorithm in Wireless Sensor Networks for Dangerous Chemicals Monitoring2023 12th International Conference of Information and Communication Technology (ICTech)10.1109/ICTech58362.2023.00105(537-544)Online publication date: Apr-2023
      • (2023)RTM: Realistic Weight-Based Reliable Trust Model for Large Scale WSNsWireless Personal Communications: An International Journal10.1007/s11277-022-10165-7129:2(953-991)Online publication date: 11-Jan-2023
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