Cost-Efficient Server Configuration and Placement for Mobile Edge Computing

Abstract

Computing resource configuration and site selection of edge servers (ESs) are two critical steps to build up a mobile edge computing (MEC) platform. In this paper, the joint optimization problem of configuration and placement for ES in the MEC environment is investigated. First, we treat each ES as an M/G/m queueing model, and establish mathematical models to characterize the MEC environment, such that the performance and operational expenditures (OPEX) of the system can be calculated analytically. Then, we design a two-stage method and develop a series of algorithms based on bisection algorithm and genetic algorithm (GA) to obtain the optimal configuration scheme and sub-optimal placement scheme (including the deployment quantity) of ESs, with the goal of minimizing OPEX while maintaining system performance at a predetermined level. Finally, we conduct experiments based on a real base station dataset provided by Shanghai Telecom to show the effectiveness of the proposed algorithms. To the best of our knowledge, this work is the first research of the joint optimization problem of configuration and placement for ES in the MEC environment, where the main objective is to increase the cost efficiency.