Joint Offloading and Computation Energy Efficiency Maximization in a Mobile Edge Computing System

TLDR: A new algorithm to evaluate the performance of the mobile edge computing system is proposed and it is revealed that when data size is small, local computing plays a more important role, but when the size grows, data offloading becomes preferable.

Abstract: This paper proposes a new algorithm to evaluate the performance of the mobile edge computing system. Specifically, a new metric called computation efficiency is defined as the number of calculated data bits divided by the corresponding energy consumption. In order to compute the required data timely, we combine two schemes, local computing and data offloading, into a joint computation algorithm. An optimization problem is formulated with the objective to maximize the sum of computation efficiency among users with weighting factors. With iterative and gradient descent methods, the problem can be solved efficiently. Simulation results show that the proposed scheme outperforms traditional approaches. In addition, the tradeoff study between local computing and data offloading reveals that when data size is small, local computing plays a more important role, but when the size grows, data offloading becomes preferable.