Enhanced Harris Hawk multi-objective optimization algorithm for cognitive radio-vehicular ad hoc networks
Enhanced Harris Hawk multi-objective optimization algorithm for cognitive radio-vehicular ad hoc networks
Author(s): Md. Asif HossainSubject(s): Business Economy / Management, Energy and Environmental Studies, Human Geography, Methodology and research technology, ICT Information and Communications Technologies, Transport / Logistics
Published by: Žilinská univerzita v Žilině
Keywords: cognitive radio; Vehicular Ad hoc Networks (VANETS); multi-objective optimization; Harris Hawk optimization (HHO); hardware-in-the-loop experiments; spectrum allocation;
Summary/Abstract: In this paper is presented an Enhanced Harris Hawk Multi-Objective Optimization (EH-HHO) algorithm for joint spectrum allocation, interference mitigation, and energy efficiency optimization in Cognitive Radio–Vehicular Ad Hoc Networks (CR-VANETs). EH-HHO integrates adaptive exploration, dynamic switching, and crowding-distance preservation to avoid premature convergence and obtain well-distributed Pareto-optimal solutions. Extensive simulations, using the SUMO–OMNeT++, VEINS/ns-3, and hardware-in-the-loop experiments, show superior spectrum utilization, energy savings, and convergence speed compared to NSGA-II and MOPSO. Statistical validation confirms performance significance, highlighting the EH-HHO as an efficient non–deep learning framework for CR-VANET optimization.
Journal: Komunikácie - vedecké listy Žilinskej univerzity v Žiline
- Issue Year: 28/2026
- Issue No: 2
- Page Range: 5021-5032
- Page Count: 11
- Language: English
