How Close to the Edge? Delay/utilization tradeoffs in MEC

TL;DR

This paper investigates the tradeoffs between delay and utilization in mobile edge computing (MEC) by analyzing large-scale crowd-sourced data, revealing opportunities for optimizing server use and latency depending on deployment strategies.

Contribution

It provides the first empirical analysis of delay and utilization tradeoffs in MEC using real-world data from multiple cities and operators.

Findings

High server utilization is achievable with MEC.

Low application latency can be maintained alongside high utilization.

Optimal strategies depend on geographic and deployment specifics.

Abstract

Virtually all of the rapidly increasing data traffic consumed by mobile users requires some kind of processing, normally performed at cloud servers. A recent thrust, {\em mobile edge computing}, moves such processing to servers {\em within} the cellular mobile network. The large temporal and spatial variations to which mobile data usage is subject could make the reduced latency that edge clouds offer come at an unacceptable cost in redundant and underutilized infrastructure. We present some first empirical results on this question, based on large scale sampled crowd-sourced traces from several major cities spanning multiple operators and identifying the applications in use. We find opportunities to obtain both high server utilization and low application latency, but the best approaches will depend on the individual network operator's deployment strategy and geographic specifics of the cities we study.