A Greedy Algorithm for Task Offloading in Mobile Edge Computing System

Mobile edge computing (MEC) is a novel technique that can reduce mobiles' computational burden by tasks offloading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless channels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First (SMSEF) algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.