Enhanced Honey Badger Algorithm for mesh routers placement problem in wireless mesh networks

Sylia Mekhmoukh Taleb, Yassine Meraihi, Seyedali Mirjalili, Dalila Acheli, Amar Ramdane-Cherif, Asma Benmessaoud Gabis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper proposes an improved version of the newly developed Honey Badger Algorithm (HBA), called Generalized opposition Based-Learning HBA (GOBL-HBA), for solving the mesh routers placement problem. The proposed GOBLHBA is based on the integration of the generalized opposition-based learning strategy into the original HBA. GOBL-HBA is validated in terms of three performance metrics such as user coverage, network connectivity, and fitness value. The evaluation is done using various scenarios with different number of mesh clients, number of mesh routers, and coverage radius values. The simulation results revealed the efficiency of GOBL-HBA when compared with the classical HBA, Genetic Algorithm (GA), and Particle Swarm optimization (PSO).

Original languageEnglish
Title of host publicationICAASE 2022 - 5th Edition of the International Conference on Advanced Aspects of Software Engineering, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665492027
DOIs
Publication statusPublished - 2022
Event5th Edition of the International Conference on Advanced Aspects of Software Engineering, ICAASE 2022 - Constantine, Algeria
Duration: 17 Sept 202218 Sept 2022

Publication series

NameICAASE 2022 - 5th Edition of the International Conference on Advanced Aspects of Software Engineering, Proceedings

Conference

Conference5th Edition of the International Conference on Advanced Aspects of Software Engineering, ICAASE 2022
Country/TerritoryAlgeria
CityConstantine
Period17/09/2218/09/22

Keywords

  • Generalized opposition based-learning
  • Honey Badger Algorithm
  • Mesh routers placement problem
  • Wireless mesh networks

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