View in EDS

A multi‐objective method for virtual machines allocation in cloud data centres using an improved grey wolf optimization algorithm.

Saved in:
Bibliographic Details
Title: A multi‐objective method for virtual machines allocation in cloud data centres using an improved grey wolf optimization algorithm.
Authors: Hashemi, Masoud1 Masoudhashemi60@yahoo.com, Javaheri, Danial2, Sabbagh, Parisa3, Arandian, Behdad4, Abnoosian, Karlo5 karlo.abnoosian@srbiau.ac.ir
Source: IET Communications (Wiley-Blackwell). Nov2021, Vol. 15 Issue 18, p2342-2353. 12p.
Subjects: Virtual machine systems, Cloud computing, Mathematical optimization, Computer simulation, Algorithms
Abstract: Cloud computing is a rapidly evolving computational technology. It is a distributed computational system that offers dynamically scaled computational resources, such as processing power, storage, and applications, delivered as a service through the Internet. Virtual machines (VMs) allocation is known as one of the most significant problems in cloud computing. It aims to find a suitable location for VMs on physical machines (PMs) to attain predefined aims. So, the main purpose is to reduce energy consumption and improve resource utilization. Because the VM allocation issue is NP‐hard, meta‐heuristic and heuristic methods are frequently utilized to address it. This paper presents an energy‐aware VM allocation method using the improved grey wolf optimization (IGWO) algorithm. Our key goals are to decrease both energy consumption and allocation time. The simulation outcomes from the MATLAB simulator approve the excellence of the algorithm compared to previous works. [ABSTRACT FROM AUTHOR]
Copyright of IET Communications (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 153313982
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A multi‐objective method for virtual machines allocation in cloud data centres using an improved grey wolf optimization algorithm.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hashemi%2C+Masoud%22">Hashemi, Masoud</searchLink><relatesTo>1</relatesTo><i> Masoudhashemi60@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Javaheri%2C+Danial%22">Javaheri, Danial</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Sabbagh%2C+Parisa%22">Sabbagh, Parisa</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Arandian%2C+Behdad%22">Arandian, Behdad</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Abnoosian%2C+Karlo%22">Abnoosian, Karlo</searchLink><relatesTo>5</relatesTo><i> karlo.abnoosian@srbiau.ac.ir</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22IET+Communications+%28Wiley-Blackwell%29%22">IET Communications (Wiley-Blackwell)</searchLink>. Nov2021, Vol. 15 Issue 18, p2342-2353. 12p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Virtual+machine+systems%22">Virtual machine systems</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Cloud computing is a rapidly evolving computational technology. It is a distributed computational system that offers dynamically scaled computational resources, such as processing power, storage, and applications, delivered as a service through the Internet. Virtual machines (VMs) allocation is known as one of the most significant problems in cloud computing. It aims to find a suitable location for VMs on physical machines (PMs) to attain predefined aims. So, the main purpose is to reduce energy consumption and improve resource utilization. Because the VM allocation issue is NP‐hard, meta‐heuristic and heuristic methods are frequently utilized to address it. This paper presents an energy‐aware VM allocation method using the improved grey wolf optimization (IGWO) algorithm. Our key goals are to decrease both energy consumption and allocation time. The simulation outcomes from the MATLAB simulator approve the excellence of the algorithm compared to previous works. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IET Communications (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=153313982
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1049/cmu2.12274
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 2342
    Subjects:
      – SubjectFull: Virtual machine systems
        Type: general
      – SubjectFull: Cloud computing
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Algorithms
        Type: general
    Titles:
      – TitleFull: A multi‐objective method for virtual machines allocation in cloud data centres using an improved grey wolf optimization algorithm.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hashemi, Masoud
      – PersonEntity:
          Name:
            NameFull: Javaheri, Danial
      – PersonEntity:
          Name:
            NameFull: Sabbagh, Parisa
      – PersonEntity:
          Name:
            NameFull: Arandian, Behdad
      – PersonEntity:
          Name:
            NameFull: Abnoosian, Karlo
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2021
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-print
              Value: 17518628
          Numbering:
            – Type: volume
              Value: 15
            – Type: issue
              Value: 18
          Titles:
            – TitleFull: IET Communications (Wiley-Blackwell)
              Type: main
ResultId 1