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A hybrid algorithm to reduce energy consumption management in cloud data centers

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 1 (2019)

DOI
10.11591/ijece.v9i1.pp554-561
ISSN
2088-8708, 2088-8708
Published
2019-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • Sharif University of Technology
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>A hybrid algorithm to reduce energy consumption management in cloud data centers</dc:title><dc:creator>Tarahomi, Mehran</dc:creator><dc:creator>Izadi, Mohammad</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i1.pp554-561</dc:identifier><dc:identifier>10.11591/ijece.v9i1.pp554-561</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 1 (2019); 554</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/8250/11085</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>