Energy optimization using virtual machine migration for power aware

Sukhesh Kothari; Chandan Parsad; Shubham Mahajan; Laith Abualigah

doi:10.54254/2755-2721/17/20230933

Research Article

Open access

Published on 23 October 2023

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Kothari,S.;Parsad,C.;Mahajan,S.;Abualigah,L. (2023). Energy optimization using virtual machine migration for power aware. Applied and Computational Engineering,17,169-175.

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Energy optimization using virtual machine migration for power aware

Sukhesh Kothari ¹, Chandan Parsad ², Shubham Mahajan ³, Laith Abualigah *^,4,

¹ Ajeenkya D Y Patil University
² Ajeenkya D Y Patil University
³ Ajeenkya D Y Patil University; Chandigarh University
⁴ Al al-Bayt University; Al-Ahliyya Amman University; Middle East University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/17/20230933

Abstract

Using cloud computing, the cloud service can be delivered to the user via an internet connection. A major concept in cloud computing is virtualization, which allows for the dynamic sharing of physical resources. The deployment of virtual machines (VMs) in the cloud is a difficult problem since they are placed on top of real machines in the data center. A good VM placement policy should increase resource utilization and also provide energy optimization, as saving energy has become crucial due to the high demand for the cloud and its data centers consuming high power. In this work, an approach is made to optimize the energy consumption during VM migration called, Power-Aware Energy Optimized VM Migration (PAEOVMM). The approach uses the maxPower of the host to allocate VM to the host. Our proposed approach is analyzed using CloudSim. As per the simulation results, PAEOVVM performs better in energy consumption than existing baseline CloudSim algorithm. PAEOVVM performs improvement in energy consumption on an average of 27-40%.

Keywords

cloud computing, servers, power consumption, energy consumption, service virtualization, virtual machines, virtual machine migration, data centers, energy-awareness

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Cite this article

Kothari,S.;Parsad,C.;Mahajan,S.;Abualigah,L. (2023). Energy optimization using virtual machine migration for power aware. Applied and Computational Engineering,17,169-175.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

Conference website: https://2023.confcds.org/

ISBN：978-1-83558-025-7(Print) / 978-1-83558-026-4(Online)

Conference date: 14 July 2023

Editor：Roman Bauer, Marwan Omar, Alan Wang

Series: Applied and Computational Engineering

Volume number: Vol.17

ISSN：2755-2721(Print) / 2755-273X(Online)

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