A Cost-Effective Deadline-Constrained Dynamic Scheduling Algorithm for Scientific Workflows in a Cloud Environment

Cloud computing, a distributed computing paradigm, enables delivery of IT resources over the Internet and follows the pay-as-you-go billing model. Workflow scheduling is one of the most challenging problems in cloud computing. Although, workflow scheduling on distributed systems like grids and clust...

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Published in:	IEEE transactions on cloud computing Vol. 6; no. 1; pp. 2 - 18
Main Authors:	Sahni, Jyoti, Vidyarthi, Deo Prakash
Format:	Journal Article
Language:	English
Published:	IEEE Computer Society 01.01.2018
Subjects:	Cloud computing Computational modeling Data models Delays Dynamic scheduling Processor scheduling quality of service (QoS) resource provisioning Schedules scheduling scientific workflows
ISSN:	2168-7161, 2372-0018
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Abstract	Cloud computing, a distributed computing paradigm, enables delivery of IT resources over the Internet and follows the pay-as-you-go billing model. Workflow scheduling is one of the most challenging problems in cloud computing. Although, workflow scheduling on distributed systems like grids and clusters have been extensively studied, however, these solutions are not viable for a cloud environment. It is because, a cloud environment differs from other distributed environment in two major ways: on-demand resource provisioning and pay-as-you-go pricing model. Thus, to achieve the true benefits of workflow orchestration onto cloud resources novel approaches that can capitalize the advantages and address the challenges specific to a cloud environment needs to be developed. This work proposes a dynamic cost-effective deadline-constrained heuristic algorithm for scheduling a scientific workflow in a public cloud. The proposed technique aims to exploit the advantages offered by cloud computing while taking into account the virtual machine (VM) performance variability and instance acquisition delay to identify a just-in-time schedule of a deadline constrained scientific workflow at lesser costs. Performance evaluation on some well-known scientific workflows exhibit that the proposed algorithm delivers better performance in comparison to the current state-of-the-art heuristics.
AbstractList	Cloud computing, a distributed computing paradigm, enables delivery of IT resources over the Internet and follows the pay-as-you-go billing model. Workflow scheduling is one of the most challenging problems in cloud computing. Although, workflow scheduling on distributed systems like grids and clusters have been extensively studied, however, these solutions are not viable for a cloud environment. It is because, a cloud environment differs from other distributed environment in two major ways: on-demand resource provisioning and pay-as-you-go pricing model. Thus, to achieve the true benefits of workflow orchestration onto cloud resources novel approaches that can capitalize the advantages and address the challenges specific to a cloud environment needs to be developed. This work proposes a dynamic cost-effective deadline-constrained heuristic algorithm for scheduling a scientific workflow in a public cloud. The proposed technique aims to exploit the advantages offered by cloud computing while taking into account the virtual machine (VM) performance variability and instance acquisition delay to identify a just-in-time schedule of a deadline constrained scientific workflow at lesser costs. Performance evaluation on some well-known scientific workflows exhibit that the proposed algorithm delivers better performance in comparison to the current state-of-the-art heuristics.
Author	Vidyarthi, Deo Prakash Sahni, Jyoti
Author_xml	– sequence: 1 givenname: Jyoti surname: Sahni fullname: Sahni, Jyoti email: jyoti92_scs@jnu.ac.in organization: Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India – sequence: 2 givenname: Deo Prakash surname: Vidyarthi fullname: Vidyarthi, Deo Prakash email: dpv@mail.jnu.ac organization: Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India
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SubjectTerms	Cloud computing Computational modeling Data models Delays Dynamic scheduling Processor scheduling quality of service (QoS) resource provisioning Schedules scheduling scientific workflows
Title	A Cost-Effective Deadline-Constrained Dynamic Scheduling Algorithm for Scientific Workflows in a Cloud Environment
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