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A review on various optimization techniques of resource provisioning in cloud computing

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

DOI
10.11591/ijece.v9i1.pp629-634
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

Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet.It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over-provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • Pondicherry University
  • Affiliation unknown
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  • Same organisation
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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.

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Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 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 review on various optimization techniques of resource provisioning in cloud computing</dc:title><dc:creator>Sumalatha, K.</dc:creator><dc:creator>Anbarasi, M. S.</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Cloud computing is &amp;lt;/span&amp;gt;&amp;lt;span lang="EN-AU"&amp;gt;the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;.It is a&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-AU"&amp;gt; broad and deep platform that helps customers builds sophisticated, scalable applications.&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt; To get the full benefits, research on a wide range of topics is needed. While resource over-provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning.&amp;lt;/span&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.pp629-634</dc:identifier><dc:identifier>10.11591/ijece.v9i1.pp629-634</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 1 (2019); 629</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/10791/11094</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>