Efficient Use of Recent Bio-Inspired Optimization Algorithms in Channel Utilization

Abstract

Communication Networks have significant challenges for efficient channel utilization due to the ever-increasing demand for data traffic. This paper deals with the potential of bio-inspired algorithms to optimize channel allocation and improve network performance and efficiency. Inspired by nature, bio-inspired algorithms offer a dynamic and adaptive approach to overcome many problems faced in channel utilization, allocation and congestion problems. The paper also explores recent algorithms like the Artificial Fish Swarm Algorithm (AFSA), Moth-Flame Optimizer (MFO), Grey Wolf Optimizer (GWO), Osprey Algorithm (OA), and Whale Optimization Algorithm (WOA), explaining concepts and their potential use cases in channel utilization and channel allocation. We see the workings of some of these potential algorithms and how they prove efficient when optimized for channel utilization. Multiple simulations are looked upon to understand how these optimization techniques help dynamically allocate the most suitable channel for use and improve efficiency. Finally, we discuss the current research market and future proceedings in this field.