Characterization of different user behaviors for demand response in data centers

TL;DR

This paper characterizes user behaviors in data centers to reduce energy consumption during peak times by simulating different job submission strategies and analyzing their impact on efficiency and user experience.

Contribution

It introduces an open-source plugin for Batsim to simulate user behaviors and explores four strategies for load curtailment in data centers.

Findings

Delaying jobs can reduce energy use with minimal delay impact.

Reconfiguring jobs offers significant load reduction under certain conditions.

User involvement strategies vary in effectiveness based on system state.

Abstract

Digital technologies are becoming ubiquitous while their impact increases. A growing part of this impact happens far away from the end users, in networks or data centers, contributing to a rebound effect. A solution for a more responsible use is therefore to involve the user. As a first step in this quest, this work considers the users of a data center and characterizes their contribution to curtail the computing load for a short period of time by solely changing their job submission behavior.The contributions are: (i) an open-source plugin for the simulator Batsim to simulate users based on real data; (ii) the exploration of four types of user behaviors to curtail the load during a time window namely delaying, degrading, reconfiguring or renouncing to their job submissions. We study the impact of these behaviors on four different metrics: the energy consumed during and after the time window, the mean waiting time and the mean slowdown. We also characterize the conditions under which the involvement of users is the most beneficial.