| Title | Enhanced Honey Badger Algorithm for mesh routers placement problem in wireless mesh networks |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Taleb, Sylia Mekhmoukh, Meraihi, Yassine, Mirjalili, Seyedali, Acheli, Dalila, Ramdane-Cherif, Amar, Gabis, Asma Benmessaoud |
| Conference Name | 2022 International Conference on Advanced Aspects of Software Engineering (ICAASE) |
| Keywords | composability, Generalized opposition based-learning, genetic algorithms, Honey Badger Algorithm, Learning systems, Measurement, Mesh routers placement problem, Metrics, particle swarm optimization, pubcrawl, resilience, Resiliency, simulation, Software algorithms, wireless mesh networks |
| 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). |
| DOI | 10.1109/ICAASE56196.2022.9931590 |
| Citation Key | taleb_enhanced_2022 |
Enhanced Honey Badger Algorithm for mesh routers placement problem in wireless mesh networks