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Reliable and efficient webserver management for task scheduling in edge-cloud platform

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 5 (2023)

DOI
10.11591/ijece.v13i5.pp5922-5931
ISSN
2722-2578, 2088-8708
Published
2023-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The development in the field of cloud webserver management for the execution of the workflow and meeting the quality-of-service (QoS) prerequisites in a distributed cloud environment has been a challenging task. Though, internet of things (IoT) of work presented for the scheduling of the workflow in a heterogeneous cloud environment. Moreover, the rapid development in the field of cloud computing like edge-cloud computing creates new methods to schedule the workflow in a heterogenous cloud environment to process different tasks like IoT, event-driven applications, and different network applications. The current methods used for workflow scheduling have failed to provide better trade-offs to meet reliable performance with minimal delay. In this paper, a novel web server resource management framework is presented namely the reliable and efficient webserver management (REWM) framework for the edge-cloud environment. The experiment is conducted on complex bioinformatic workflows; the result shows the significant reduction of cost and energy by the proposed REWM in comparison with standard webserver management methodology.

Collaboration network of the authors

3 authors · 2 co-authorship links

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  • KLS Gogte Institute of Technology
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Arati ShahapurkarKLS Gogte Institute of Technology1

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 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>Reliable and efficient webserver management for task scheduling in edge-cloud platform</dc:title><dc:creator>Sangani, Sangeeta</dc:creator><dc:creator>Patil, Rudragoud</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;The development in the field of cloud webserver management for the execution of the workflow and meeting the quality-of-service (QoS) prerequisites in a distributed cloud environment has been a challenging task. Though, internet of things (IoT) of work presented for the scheduling of the workflow in a heterogeneous cloud environment. Moreover, the rapid development in the field of cloud computing like edge-cloud computing creates new methods to schedule the workflow in a heterogenous cloud environment to process different tasks like IoT, event-driven applications, and different network applications. The current methods used for workflow scheduling have failed to provide better trade-offs to meet reliable performance with minimal delay. In this paper, a novel web server resource management framework is presented namely the reliable and efficient webserver management (REWM) framework for the edge-cloud environment. The experiment is conducted on complex bioinformatic workflows; the result shows the significant reduction of cost and energy by the proposed REWM in comparison with standard webserver management methodology.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-10-01</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.v13i5.pp5922-5931</dc:identifier><dc:identifier>10.11591/ijece.v13i5.pp5922-5931</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 5 (2023); 5922</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/30858/16893</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>