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Experimental analysis of task-based energy consumption in cloud computing systems

Version 2 2024-06-05, 01:56
Version 1 2016-10-12, 12:55
conference contribution
posted on 2024-06-05, 01:56 authored by Feifei ChenFeifei Chen, J Grundy, Y Yang, Jean-Guy SchneiderJean-Guy Schneider, Q He
Cloud computing delivers IT solutions as a utility to users. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A common objective of cloud providers is to develop resource provisioning and management solutions that minimise energy consumption while guaranteeing Service Level Agreements (SLAs). In order to achieve this objective, a thorough understanding of energy consumption patterns in complex cloud systems is imperative. We have developed an energy consumption model for cloud computing systems. To operationalise this model, we have conducted extensive experiments to profile the energy consumption in cloud computing systems based on three types of tasks: computation- intensive, data-intensive and communication-intensive tasks. We collected fine-grained energy consumption and performance data with varying system configurations and workloads. Our experimental results show the correlation coefficients of energy consumption, system configuration and workload, as well as system performance in cloud systems. These results can be used for designing energy consumption monitors, and static or dynamic system-level energy consumption optimisation strategies for green cloud computing systems.

History

Pagination

295-306

Location

Prague, Czech Republic

Start date

2013-04-21

End date

2013-04-24

ISBN-13

9781450316361

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2013, ACM

Title of proceedings

ICPE 2013 - Proceedings of the 2013 ACM/SPEC International Conference on Performance Engineering

Event

Performance Engineering. Conference (4th : 2013 : Prague, Czech Republic)

Publisher

ACM

Place of publication

New York, N.Y.