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Multi-objective tasks scheduling using artificial bee colony algorithm based on cellular automata in cloud computing environment

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 5 (2022)

DOI
10.11591/ijece.v12i5.pp5657-5666
ISSN
2722-2578, 2088-8708
Published
2022-09-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Due to the development of communication device technology and the need to use up-to-date infrastructure ready to respond quickly and in a timely manner to computational needs, the competition for the use of processing resources is increasing nowadays. The scheduling tasks in the cloud computing environment have been remained a challenge to access a quick and efficient solution. In this paper, the aim is to present a new tactic for allocating the available processing resources based on the artificial bee colony (ABC) algorithm and cellular automata for solving the task scheduling problem in the cloud computing network. The results show the performance of the proposed method is better than its counterparts.

Collaboration network of the authors

4 authors · 6 co-authorship links · 5 across different organisations

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  • Islamic Azad University, Tehran
  • Islamic Azad University Boroujerd Branch
  • Shahed University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

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>Multi-objective tasks scheduling using artificial bee colony algorithm based on cellular automata in cloud computing environment</dc:title><dc:creator>Salehi Babadi, Mehdi</dc:creator><dc:creator>Shiri, Mohammad Ebrahim</dc:creator><dc:creator>Moazami Goudarzi, Mohammad Reza</dc:creator><dc:creator>Haj Seyyed Javadi, Hamid</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span&amp;gt;Due to the development of communication device technology and the need to use up-to-date infrastructure ready to respond quickly and in a timely manner to computational needs, the competition for the use of processing resources is increasing nowadays. The scheduling tasks in the cloud computing environment have been remained a challenge to access a quick and efficient solution. In this paper, the aim is to present a new tactic for allocating the available processing resources based on the artificial bee colony (ABC) algorithm and cellular automata for solving the task scheduling problem in the cloud computing network. The results show the performance of the proposed method is better than its counterparts.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-09-01</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.v12i5.pp5657-5666</dc:identifier><dc:identifier>10.11591/ijece.v12i5.pp5657-5666</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 5 (2022); 5657</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/25009/16012</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>