Design of Long-Term Evolution Based Mobile Edge Computing Systems to Improve 5G Systems

Mobile edge computing is an emerging technology that enables mobile devices to access cloud services with reduced latency by moving computing, storage, and network control closer to the network edge. This advancement allows mobile devices to operate for longer periods on a single charge. With the advent of 5G communications, there is increasing interest in exploring the integration of mobile edge computing within existing mobile networks. The proposed work aims to develop a portable 5G computing system that offloads computational tasks to edge servers, thereby reducing latency and improving energy efficiency. The work focuses on designing efficient workload allocation algorithms to optimize the distribution of tasks to the supported servers. By implementing and evaluating a practical mobile-based computing system based on Long-Term Evolution (LTE), this research aims to demonstrate the real-world effectiveness of such mobile edge computing programs, with particular emphasis on reducing delays and enhancing energy efficiency.

I. Introduction

Mobile edge computing (MEC) has emerged as a promising technology that brings computing capabilities closer to the network edge, enabling faster and more efficient processing of mobile applications [1]. By leveraging the computational power and storage capacity available at the edge of the network, MEC reduces latency, enhances real-time responsiveness, and alleviates the burden on centralized cloud servers. In recent years, the proliferation of 4G networks, specifically Long-Term Evolution (LTE), has laid the foundation for advanced mobile applications and services. However, 4G systems still face challenges related to latency and energy efficiency, prompting the need for novel solutions to optimize their performance [2]–[6].