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

Feifei Chen, John Grundy, Yun Yang, Jean Guy Schneider, Qiang He

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

32 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationICPE 2013 - Proceedings of the 2013 ACM/SPEC International Conference on Performance Engineering
Number of pages12
Publication statusPublished - 2013
Externally publishedYes
EventACM/SPEC International Conference on Performance Engineering 2013 - Prague, Czech Republic
Duration: 21 Apr 201324 Apr 2013
Conference number: 4th


ConferenceACM/SPEC International Conference on Performance Engineering 2013
Abbreviated titleICPE 2013
CountryCzech Republic


  • cloud computing
  • energy consumption
  • energy efficiency
  • green cloud
  • performance analysis

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