Energy Prediction for Cloud Workload Patterns

Alzamil, I and Djemame, K (2017) Energy Prediction for Cloud Workload Patterns. In: Bañares, J, Tserpes, K and Altmann, J, (eds.) GECON 2016: Economics of Grids, Clouds, Systems, and Services. 13th International Conference on Economics of Grids, Clouds, Systems and Services (GECON'2016), 20-22 Sep 2016, Athens, Greece. Lecture Notes in Computer Science (10382). Springer , Cham, Switzerland , pp. 160-174. ISBN 978-3-319-61919-4



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Keywords: Cloud Computing; Energy Efficiency; Energy-Aware Profiling; Energy Prediction; Workload Prediction; Cloud Workload Patterns
  • Accepted: 12 July 2016
  • Published (online): 2 July 2017
  • Published: 2 July 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Funding Information:
FunderGrant number
EU - European Union610874
Depositing User: Symplectic Publications
Date Deposited: 21 Sep 2016 12:33
Last Modified: 02 Jul 2018 00:38
Status: Published
Publisher: Springer
Series Name: Lecture Notes in Computer Science
Identification Number: