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A hybrid approach for scheduling applications in cloud computing environment

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp1387-1397
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • University of Anbar
  • Different organisations
  • Same organisation
  • Affiliation unknown
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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 approach for scheduling applications in cloud computing environment</dc:title><dc:creator>Abdalkafor, Ahmed Subhi</dc:creator><dc:creator>Ali Alheeti, Khattab M.</dc:creator><dc:description>&lt;jats:p&gt;Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-04-01</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.v10i2.pp1387-1397</dc:identifier><dc:identifier>10.11591/ijece.v10i2.pp1387-1397</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 2 (2020); 1387</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/20557/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>