JoWUA

Abstract

Wireless Mobile Networks (WMN) is a pivotal technology that can advance the development of the future digital economy. WMN delivers pervasive computational power via the multitier installation of computers, ensuring reduced latencies and enhanced interaction with multi-tier 5G networks, ledgers, and machine learning. This research presents a novel methodology for improving equipment resource management for edge nodes within a multitier WMN architecture. Alongside a centralized unit, the study evaluates active radio and dispersed units integrated with edge terminals with varying computing capabilities. A customizable Bayesian optimization is employed for hardware resource management to enhance the total computing capability of a 5G-based WMN technology. Simulation findings indicate that, under specified budget limitations, the suggested strategy surpasses pseudorandom resource management for the completion rate of computing jobs. The attainable increases range from 20% to 40%, contingent upon job difficulty and the chosen budget criterion.