A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints

A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints

Many problems in cloud computing are not solvable in polynomial time and only option left is to choose approximate solution instead of optimum. Virtual Machine placement is one of such problem with resource constraints in which overall objective is to optimize multiple resources of hosts during plac...

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Main Authors: Maheshbhai Shah Darshan, Murthi M. Vinayaka, Kumar Anand
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:MATEC Web of Conferences
Online Access:https://www.matec-conferences.org/articles/matecconf/pdf/2021/04/matecconf_eureca2020_04007.pdf
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spelling doaj-f99504774a6f4ed3a382938f2d1f08d12021-01-26T08:19:49ZengEDP SciencesMATEC Web of Conferences2261-236X2021-01-013350400710.1051/matecconf/202133504007matecconf_eureca2020_04007A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource ConstraintsMaheshbhai Shah Darshan0Murthi M. Vinayaka1Kumar Anand2Reva UniversityReva UniversityM.S. Engineering CollegeMany problems in cloud computing are not solvable in polynomial time and only option left is to choose approximate solution instead of optimum. Virtual Machine placement is one of such problem with resource constraints in which overall objective is to optimize multiple resources of hosts during placement process. In this paper we have addressed this problem with large size NP-Hard instances and proposed novel local search-based approximation algorithm. This problem is not yet studied in the research community with NP hard instances. A new proposed algorithm is empirically evaluated with state-of-the-art techniques. and our algorithm has improved placement result by 18% in CPU utilization, 21% in resource contention and 26% in overall resource utilization for benchmark instances collected from azure private cloud data center.https://www.matec-conferences.org/articles/matecconf/pdf/2021/04/matecconf_eureca2020_04007.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Maheshbhai Shah Darshan
Murthi M. Vinayaka
Kumar Anand
spellingShingle Maheshbhai Shah Darshan
Murthi M. Vinayaka
Kumar Anand
A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
MATEC Web of Conferences
author_facet Maheshbhai Shah Darshan
Murthi M. Vinayaka
Kumar Anand
author_sort Maheshbhai Shah Darshan
title A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
title_short A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
title_full A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
title_fullStr A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
title_full_unstemmed A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints
title_sort novel local search-based approximation algorithm to optimize virtual machine placement with resource constraints
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2021-01-01
description Many problems in cloud computing are not solvable in polynomial time and only option left is to choose approximate solution instead of optimum. Virtual Machine placement is one of such problem with resource constraints in which overall objective is to optimize multiple resources of hosts during placement process. In this paper we have addressed this problem with large size NP-Hard instances and proposed novel local search-based approximation algorithm. This problem is not yet studied in the research community with NP hard instances. A new proposed algorithm is empirically evaluated with state-of-the-art techniques. and our algorithm has improved placement result by 18% in CPU utilization, 21% in resource contention and 26% in overall resource utilization for benchmark instances collected from azure private cloud data center.
url https://www.matec-conferences.org/articles/matecconf/pdf/2021/04/matecconf_eureca2020_04007.pdf
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AT murthimvinayaka novellocalsearchbasedapproximationalgorithmtooptimizevirtualmachineplacementwithresourceconstraints
AT kumaranand novellocalsearchbasedapproximationalgorithmtooptimizevirtualmachineplacementwithresourceconstraints
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