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Efficient Task Scheduling and Fair Load Distribution Among Federated Clouds

Journal of ICT Research and Applications (JICTRA) · Vol. 15 No. 3 (2021) · pp. 216–238

DOI
10.5614/itbj.ict.res.appl.2021.15.3.2
ISSN
2338-5499, 2337-5787
Published
2021-12-28
Publisher
DRI - ITB
Language
eng

Abstract

The federated cloud is the future generation of cloud computing, allowing sharing of computing and storage resources, and servicing of user tasks among cloud providers through a centralized control mechanism. However, a great challenge lies in the efficient management of such federated clouds and fair distribution of the load among heterogeneous cloud providers. In our proposed approach, called QPFS_MASG, at the federated cloud level, the incoming tasks queue are partitioned in order to achieve a fair distribution of the load among all cloud providers of the federated cloud. Then, at the cloud level, task scheduling using the Modified Activity Selection by Greedy (MASG) technique assigns the tasks to different virtual machines (VMs), considering the task deadline as the key factor in achieving good quality of service (QoS). The proposed approach takes care of servicing tasks within their deadline, reducing service level agreement (SLA) violations, improving the response time of user tasks as well as achieving fair distribution of the load among all participating cloud providers. The QPFS_MASG was implemented using CloudSim and the evaluation result revealed a guaranteed degree of fairness in service distribution among the cloud providers with reduced response time and SLA violations compared to existing approaches. Also, the evaluation results showed that the proposed approach serviced the user tasks with minimum number of VMs.

Keywords

Collaboration network of the authors

9 authors · 19 co-authorship links

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  • B.M.S. College of Engineering
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
C. B. YogeeshaAffiliation unknown1
M VaishnaviB.M.S. College of Engineering1
Yashita JainB.M.S. College of Engineering1
B V RamyashreeB.M.S. College of Engineering1
Arpith KumarB.M.S. College of Engineering1
Nandhini VineethB.M.S. College of Engineering1

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.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 1 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Efficient Task Scheduling and Fair Load Distribution Among Federated Clouds </dc:title>
	<dc:creator>B S, Rajeshwari</dc:creator>
	<dc:creator>Dakshayini, M.</dc:creator>
	<dc:creator>Guruprasad, H.S.</dc:creator>
	<dc:subject xml:lang="en-US">cloud computing</dc:subject>
	<dc:subject xml:lang="en-US">fair load distribution</dc:subject>
	<dc:subject xml:lang="en-US">federated cloud</dc:subject>
	<dc:subject xml:lang="en-US">service level agreement</dc:subject>
	<dc:subject xml:lang="en-US">task scheduling</dc:subject>
	<dc:description xml:lang="en-US">The federated cloud is the future generation of cloud computing, allowing sharing of computing and storage resources, and servicing of user tasks among cloud providers through a centralized control mechanism. However, a great challenge lies in the efficient management of such federated clouds and fair distribution of the load among heterogeneous cloud providers. In our proposed approach, called QPFS_MASG, at the federated cloud level, the incoming tasks queue are partitioned in order to achieve a fair distribution of the load among all cloud providers of the federated cloud. Then, at the cloud level, task scheduling using the Modified Activity Selection by Greedy (MASG) technique assigns the tasks to different virtual machines (VMs), considering the task deadline as the key factor in achieving good quality of service (QoS). The proposed approach takes care of servicing tasks within their deadline, reducing service level agreement (SLA) violations, improving the response time of user tasks as well as achieving fair distribution of the load among all participating cloud providers. The QPFS_MASG was implemented using CloudSim and the evaluation result revealed a guaranteed degree of fairness in service distribution among the cloud providers with reduced response time and SLA violations compared to existing approaches. Also, the evaluation results showed that the proposed approach serviced the user tasks with minimum number of VMs.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2021-12-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/16684</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2021.15.3.2</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 15 No. 3 (2021); 216-238</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2021.15.3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/16684/5559</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Journal of ICT Research and Applications</dc:rights>
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