Solving the mesh router nodes placement in wireless mesh networks using coyote optimization algorithm

Sylia Mekhmoukh Taleb, Yassine Meraihi, Asma Benmessaoud Gabis, Seyedali Mirjalili, Atef Zaguia, Amar Ramdane-Cherif

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Wireless Mesh Networks (WMNs) have rapid real developments during the last decade due to their simple implementation at low cost, easy network maintenance, and reliable service coverage. Despite these properties, the nodes placement of such networks imposes an important research issue for network operators and influences strongly the WMNs performance. This challenging issue is known to be an NP-hard problem, and solving it using approximate optimization algorithms (i.e. heuristic and meta-heuristic) is essential. This motivates our attempts to present an application of the Coyote Optimization Algorithm (COA) to solve the mesh routers placement problem in WMNs in this work. Experiments are conducted on several scenarios under different settings, taking into account two important metrics such as network connectivity and user coverage. Simulation results demonstrate the effectiveness and merits of COA in finding optimal mesh routers locations when compared to other optimization algorithms such as Firefly Algorithm (FA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), Bat Algorithm (BA), African Vulture Optimization Algorithm (AVOA), Aquila Optimizer (AO), Bald Eagle Search optimization (BES), Coronavirus herd immunity optimizer (CHIO), and Salp Swarm Algorithm (SSA).

Original languageEnglish
JournalIEEE Access
Publication statusAccepted/In press - 2022


  • Costs
  • Coyote Optimization Algorithm
  • Genetic algorithms
  • Heuristic algorithms
  • Measurement
  • Mesh Router Nodes Placement
  • Meta-heuristics
  • Network Design
  • Optimization
  • Topology
  • Wireless mesh networks
  • Wireless Mesh Networks


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