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Evolutionary and noise-aware data gathering for wireless sensor networks

  • University of Massachusetts Boston
  • Chiang Mai University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN.

Original languageEnglish
Title of host publicationBio-Inspired Models of Network, Information, and Computing Systems - 5th International ICST Conference, BIONETICS 2010, Revised Selected Papers
Pages32-39
Number of pages8
DOIs
StatePublished - 2012
Event5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems, BIONETICS 2010 - Boston, MA, United States
Duration: Dec 1 2010Dec 3 2010

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume87 LNICST
ISSN (Print)1867-8211

Conference

Conference5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems, BIONETICS 2010
Country/TerritoryUnited States
CityBoston, MA
Period12/1/1012/3/10

ASJC Scopus Subject Areas

  • Computer Networks and Communications

Keywords

  • Data gathering protocol
  • Genetic algorithm
  • Noisy multiobjective optimization problem
  • Wireless sensor networks

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