Performance and Energy-based Cost Prediction of Virtual Machines Live Migration in Clouds

Mohammad Aldossary, Karim Djemame

2018

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.

Paper Citation

in Harvard Style

Aldossary M. and Djemame K. (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 - Volume 1: CLOSER, ISBN 978-989-758-295-0, pages 384-391. DOI: 10.5220/0006682803840391

in Bibtex Style

@conference{closer18,
author={Mohammad Aldossary and Karim Djemame},
title={Performance and Energy-based Cost Prediction of Virtual Machines Live Migration in Clouds},
booktitle={Proceedings of the 8th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2018},
pages={384-391},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006682803840391},
isbn={978-989-758-295-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Performance and Energy-based Cost Prediction of Virtual Machines Live Migration in Clouds
SN - 978-989-758-295-0
AU - Aldossary M.
AU - Djemame K.
PY - 2018
SP - 384
EP - 391
DO - 10.5220/0006682803840391