Aldossary, M and Djemame, K orcid.org/0000-0001-5811-5263 (2018) Performance and Energy-based Cost Prediction of Virtual Machines Live Migration in Clouds. In: Proceedings of the 8th International Conference on Cloud Computing and Services Science. 8th International Conference on Cloud Computing and Services Science, CLOSER 2018, 19-21 Mar 2018, Funchal, Madeira, Portugal. SciTePress , pp. 384-391. ISBN 978-989-758-295-0
Abstract
Virtual Machines (VMs) live migration is one of the important approaches to improve resource utilisation and support energy efficiency in Clouds. However, VMs live migration leads to performance loss and additional costs due to increased migration time and energy overhead. This paper introduces a Performance and Energy-based Cost Prediction Framework to estimate the total cost of VMs live migration by considering the resource usage and power consumption, while maintaining the expected level of performance. A series of experiments conducted on a Cloud testbed show that this framework is capable of predicting the workload, power consumption and total cost for heterogeneous VMs before and after live migration, with the possibility of recovering the migration cost e.g. 28.48% for the predicted cost recovery of the VM.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Cloud Computing; Cost Prediction; Workload Prediction; Live Migration; Power Consumption |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 687584 |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 May 2018 13:30 |
Last Modified: | 11 May 2018 13:30 |
Status: | Published |
Publisher: | SciTePress |
Identification Number: | 10.5220/0006682803840391 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130672 |