AI WIRELESS BANDWIDTH OPTIMIZATIO

Abstract

AI WIRELESS BANDWIDTH OPTIMIZATION, is crucial in wireless networks to maximize throughput, minimize latency, and enhance overall network performance. In this study, we explore the application of two nature-inspired optimization algorithms, namely Whale Optimization Algorithm (WOA) and Particle Swarm Optimization Algorithm (PSO), to optimize the bandwidth allocation in wireless networks. The objective of the study is to improve the network’s bandwidth utilization by finding an optimal allocation scheme for different network resources. The WOA and PSO algorithms are selected due to their ability to efficiently search large solution spaces and find near-optimal solutions. The proposed methodology involves several steps. Firstly, an objective function is defined, which quantifies the desired performance metric, such as maximizing throughput or minimizing latency. The algorithms are then initialized with appropriate parameters, including the number of whales or particles, maximum iterations, and solution space boundaries. The population of potential solutions is randomly initialized, and the fitness of each solution is evaluated by calculating the objective function value. The best solution found so far is tracked and updated whenever a better solution is discovered. The algorithms’ specific update equations and search operators are applied iteratively to guide the search towards promising solutions. The optimization process continues until a termination condition is met, such as reaching the maximum number of iterations or achieving a satisfactory solution. The algorithm’s performance is assessed by analyzing the obtained results, including the best solution found and its corresponding fitness value. By leveraging the WOA and PSO algorithms, this study aims to provide an effective ap proach for optimizing bandwidth allocation in wireless networks. The proposed methodology can contribute to enhancing network performance, reducing congestion, and improving user experience by efficiently utilizing available resources