Quasi-Affine Transformation Evolutionary Algorithm With Communication Schemes for Application of RSSI in Wireless Sensor Networks

Zhi-Gang Du, Jeng-Shyang Pan, Shu-Chuan Chu, Han-Jiang Luo, Pei Hu

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

QUasi-Affine TRansformation Evolutionary algorithm (QUATRE) is a new optimization algorithm based on population for complex multiple real parameter optimization problems in real world. In this paper, a novel multi-group multi-choice communication strategy algorithm for QUasi-Affine TRansformation Evolutionary (MM-QUATRE) algorithm is proposed to solve the disadvantage that the original QUATRE is always easily to fall into local optimization in the strategy of updating bad nodes with multiple groups and multiple choices. We compared it with other intelligent algorithms, the most advanced PSO variant, parallel PSO (P-PSO) variant, native QUATRE and parallel QUATRE (P-PSO) under CEC2013 large-scale optimization test suite. Thus, the performance of MM-QUATRE was verified. The conclusion that the MM-QUATRE algorithm is superior to other intelligent algorithms is proved by the experimental results. In addition, the application results of MM-QUATRE algorithm (MM-QUATRE-RSSI) based on RSSI in WSN node localization were analyzed and studied. The results appear that this method has higher localization accuracy than other similar algorithms.

Original languageEnglish
Article number8952709
Pages (from-to)8583-8594
Number of pages12
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 8 Jan 2020
Externally publishedYes

Bibliographical note

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/

Keywords

  • affine transforms
  • evolutionary computation
  • particle swarm optimisation
  • RSSI
  • sensor placement
  • wireless sensor networks
  • bad point update
  • P-PSO
  • WSN
  • MM-QUATRE
  • PSO
  • QUATRE

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