Energy Trade-off for Computation Offloading in Mobile Edge Computing

Mobile devices (MDs) have a number of restrictions in terms of battery life, processing power, and storage space due to the growing demand for larger computational capabilities in application. Offloading computationally demanding work to MEC servers has been an answer to this problem. By considering several variables such as distance, transmission rate, CPU frequency, and transmission power, we did some simulations to assess the effectiveness of various offloading scenarios. The energy trade-off involved in this process was examined in this research with a focus on the possible energy savings provided by offloading. To optimize energy consumption in MEC systems, this study examined the advantages and drawbacks of offloading.

I. Introduction

The rapid growth of new applications such as image processing, face recognition, virtual reality, augmented reality, and real-time online games has created a demand for large computing capabilities. In recent years, the use of MDs to run various applications has become an integral part of human life. Mobile devices, however, are constrained by their limited battery capacities, computing capacities, and storage capacities, making them unsuitable for running applications with computationally intensive tasks [1]. To address this challenge, the solution lies in offloading these tasks to MEC servers.