Scalability of a novel shifting balance theory-based optimization algorithm: a comparative study on a cluster-based wireless sensor network

Erfu Yang, Nick H. Barton, Tughrul Arslan, Ahmet T. Erdogan

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

1 Citation (Scopus)

Abstract

Scalability is one of the most important issues for optimization algorithms used in wireless sensor networks (WSNs) since there are often many parameters to be optimized at the same time. In this case it is very hard to ensure that an optimization algorithm can be smoothly scaled up from a low-dimensional optimization problem to the one with a high dimensionality. This paper addresses the scalability issue of a novel optimization algorithm inspired by the Shifting Balance Theory (SBT) of evolution in population genetics. Toward this end, a cluster-based WSN is employed in this paper as a benchmark to perform a comparative study. The total energy consumption is minimized under the required quality of service by jointly optimizing the transmission power and rate for each sensor node. The results obtained by the SBT-based algorithm are compared with the Metropolis algorithm (MA) and currently popular particle swarm optimizer (PSO) to assess the scaling performance of the three algorithms against the same WSN optimization problem.

Original languageEnglish
Title of host publicationEvolvable Systems: From Biology to Hardware
Subtitle of host publication8th International Conference, ICES 2008, Prague, Czech Republic, September 21-24, 2008. Proceedings
Place of PublicationBerlin
Pages249-260
Number of pages12
DOIs
Publication statusPublished - 8 Sep 2008
Event8th International Conference on Evolvable Systems: From Biology to Hardware, ICES 2008 - Prague, United Kingdom
Duration: 21 Sep 200824 Sep 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume5216
ISSN (Print)0302-9743

Conference

Conference8th International Conference on Evolvable Systems: From Biology to Hardware, ICES 2008
CountryUnited Kingdom
CityPrague
Period21/09/0824/09/08

Keywords

  • cluster-based
  • comparative studies
  • high dimensionality
  • metropolis algorithms
  • optimization algorithms
  • optimization problems
  • particle swarm optimizers
  • population genetics
  • scalability issue
  • shifting balance theory
  • total energy consumption
  • transmission power
  • WSN optimization

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