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Authors: Mohamed Esam Elsaid 1 ; Hazem M. Abbas 2 and Christoph Meinel 1

Affiliations: 1 Internet Technologien und Systeme, Hasso-Plattner Institut, Potsdam Uni., Potsdam, Germany ; 2 Dept. Computer and Systems Engineering, Ain Shams University, Cairo, Egypt

Keyword(s): Timing, Cloud Computing, Virtual, Live Migration, VMware, vMotion, Modeling, Overhead, Cost, Datacenter, Prediction, Machine Learning.

Abstract: Live migation of Virtual Machines (VMs) is a vital feature in virtual datacenters and cloud computing platforms. Pre-copy live migration techniques is the commonly used technique in virtual datacenters hypervisors including VMware, Xen, Hyper-V and KVM. This is due to the robustness of pre-copy technique compared to post-copy or hybrid-copy techniques. The disadvantage of pre-copy live migration type is the challenge to predict the live migration cost and performance. So, virtual datanceters admins run live migration without an idea about the expected cost and the optimal timing for running live migration especially for large VMs or for multiple VMs running concurrently. This leads to longer live migration duration, network bottlenecks and live migration failure in some cases. In this paper, we use machine learning techniques to predict the optimal timing for running a live migration request. This optimal timing approach is based on using machine learning for live migration cost pred iction and datacenter network utilization prediction. Datacenter admins can be alerted with this optimal timing recommendation when a live migration request is issued. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Elsaid, M.; Abbas, H. and Meinel, C. (2020). Live Migration Timing Optimization for VMware Environments using Machine Learning Techniques. In Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-424-4; ISSN 2184-5042, SciTePress, pages 91-102. DOI: 10.5220/0009397300910102

@conference{closer20,
author={Mohamed Esam Elsaid. and Hazem M. Abbas. and Christoph Meinel.},
title={Live Migration Timing Optimization for VMware Environments using Machine Learning Techniques},
booktitle={Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER},
year={2020},
pages={91-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009397300910102},
isbn={978-989-758-424-4},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER
TI - Live Migration Timing Optimization for VMware Environments using Machine Learning Techniques
SN - 978-989-758-424-4
IS - 2184-5042
AU - Elsaid, M.
AU - Abbas, H.
AU - Meinel, C.
PY - 2020
SP - 91
EP - 102
DO - 10.5220/0009397300910102
PB - SciTePress