A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing

Migration of Virtual Machine (VM) is a critical challenge in cloud computing. The process to move VMs or applications from one Physical Machine (PM) to another is known as VM migration. In VM migration several issues should be considered. One of the major issues in VM migration problem is selecting...

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Main Authors: Seyedeh Roudabeh Hosseini, Sepideh Adabi, Reza Tavoli
Format: Article
Language:English
Published: Science and Research Branch,Islamic Azad University 2015-10-01
Series:Journal of Advances in Computer Engineering and Technology
Subjects:
Online Access:http://jacet.srbiau.ac.ir/article_8040_1e19d5de7fc651b22def4c4e4a3f5bda.pdf
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author Seyedeh Roudabeh Hosseini
Sepideh Adabi
Reza Tavoli
author_facet Seyedeh Roudabeh Hosseini
Sepideh Adabi
Reza Tavoli
author_sort Seyedeh Roudabeh Hosseini
collection DOAJ
description Migration of Virtual Machine (VM) is a critical challenge in cloud computing. The process to move VMs or applications from one Physical Machine (PM) to another is known as VM migration. In VM migration several issues should be considered. One of the major issues in VM migration problem is selecting an appropriate PM as a destination for a migrating VM. To face this issue, several approaches are proposed that focus on ranking potential destination PMs by addressing migration objectives. In this paper we propose a new hierarchal fuzzy logic system for ranking potential destination PMs for a migrating VM by considering following parameters: Performance efficiency, Communication cost between VMs, Power consumption, Workload, Temperature efficiency and Availability. Using hierarchal fuzzy logic systems which consider the mentioned six parameters which have great role in ranking of potential destination PMs for a migrating VM together, the accuracy of PMs ranking approach is increased, furthermore the number of fuzzy rules in the system are reduced, thereby reducing the computational time (which is critical in cloud environment). In our experiments, we compare our proposed approach that is named as (HFLSRPM: Hierarchal Fuzzy Logic Structure for Ranking potential destination PMs for a migrating VM) with AppAware algorithm in terms of communication cost and performance efficiency. The results demonstrate that by considering more effective parameters in the proposed PMs ranking approach, HFLSRPM outperforms AppAware algorithm.
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spelling doaj.art-8c388c3877e046c8b274f76dd831d7b72022-12-21T22:09:13ZengScience and Research Branch,Islamic Azad UniversityJournal of Advances in Computer Engineering and Technology2423-41922423-42062015-10-011323328040A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud ComputingSeyedeh Roudabeh Hosseini0Sepideh Adabi1Reza Tavoli2Department of Electronic and Computer Engineering, Institute for Higher Education Pouyandegan Danesh, Chalous, IranDepartment of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, IRANDepartment of Mathematics, Chalous Branch, Islamic Azad University, Chalous, IRANMigration of Virtual Machine (VM) is a critical challenge in cloud computing. The process to move VMs or applications from one Physical Machine (PM) to another is known as VM migration. In VM migration several issues should be considered. One of the major issues in VM migration problem is selecting an appropriate PM as a destination for a migrating VM. To face this issue, several approaches are proposed that focus on ranking potential destination PMs by addressing migration objectives. In this paper we propose a new hierarchal fuzzy logic system for ranking potential destination PMs for a migrating VM by considering following parameters: Performance efficiency, Communication cost between VMs, Power consumption, Workload, Temperature efficiency and Availability. Using hierarchal fuzzy logic systems which consider the mentioned six parameters which have great role in ranking of potential destination PMs for a migrating VM together, the accuracy of PMs ranking approach is increased, furthermore the number of fuzzy rules in the system are reduced, thereby reducing the computational time (which is critical in cloud environment). In our experiments, we compare our proposed approach that is named as (HFLSRPM: Hierarchal Fuzzy Logic Structure for Ranking potential destination PMs for a migrating VM) with AppAware algorithm in terms of communication cost and performance efficiency. The results demonstrate that by considering more effective parameters in the proposed PMs ranking approach, HFLSRPM outperforms AppAware algorithm.http://jacet.srbiau.ac.ir/article_8040_1e19d5de7fc651b22def4c4e4a3f5bda.pdfCloud computingHierarchal fuzzy logic structurevirtual machine migration
spellingShingle Seyedeh Roudabeh Hosseini
Sepideh Adabi
Reza Tavoli
A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
Journal of Advances in Computer Engineering and Technology
Cloud computing
Hierarchal fuzzy logic structure
virtual machine migration
title A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
title_full A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
title_fullStr A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
title_full_unstemmed A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
title_short A Near Optimal Approach in Choosing The Appropriate Physical Machines for Live Virtual Machines Migration in Cloud Computing
title_sort near optimal approach in choosing the appropriate physical machines for live virtual machines migration in cloud computing
topic Cloud computing
Hierarchal fuzzy logic structure
virtual machine migration
url http://jacet.srbiau.ac.ir/article_8040_1e19d5de7fc651b22def4c4e4a3f5bda.pdf
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