QGAC: Quantum Genetic Based-Clustering Algorithm for WSNs

Mechta Djamila, Harous Saad

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

1 Citation (Scopus)

Abstract

In this paper, we present a novel approach for clustering based on quantum genetic computing and complex systems. The main idea is the use of Wireless Sensor Networks (WSNs) as complex system, and Quantum Computing algorithms (QC) as research strategy. WSNs are a set of sensors that operate in parallel and interact with their neighbors using single hop or multi-hops communication. The problem with WSNs is to find, within a large set of sensors randomly deployed, the subset of best clusters and their Cluster Heads (CHs) and ensure their balanced distribution in network. To cope with this NP-hard problem, we propose a new Quantum Genetic Clustering Algorithm (QGCA) which is based on Quantum Genetic Algorithm (QGA) for CHs selection to reduce energy consumption and extend the network lifetime. A comparison is made between classical routing protocol LEACH and the proposed QGCA. Experiments show that the efficiency of QGCA is significantly better and clearly indicate that the proposed approach outperforms random CHs selection and leads to significant increase in network lifetime.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Electro/Information Technology, EIT 2018
PublisherIEEE Computer Society
Pages430-436
Number of pages7
ISBN (Electronic)9781538653982
DOIs
Publication statusPublished - Oct 18 2018
Event2018 IEEE International Conference on Electro/Information Technology, EIT 2018 - Rochester, United States
Duration: May 3 2018May 5 2018

Publication series

NameIEEE International Conference on Electro Information Technology
Volume2018-May
ISSN (Print)2154-0357
ISSN (Electronic)2154-0373

Other

Other2018 IEEE International Conference on Electro/Information Technology, EIT 2018
Country/TerritoryUnited States
CityRochester
Period5/3/185/5/18

Keywords

  • Cluster-heads selection
  • Genetic Algorithm
  • Quantum Computing
  • Wireless Sensor Networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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