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Future Internet 2018, 10(1), 5; https://doi.org/10.3390/fi10010005

Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments

1
School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China
2
Department of Computer Science, University of Education, Lahore 54770, Pakistan
*
Author to whom correspondence should be addressed.
Received: 19 November 2017 / Revised: 23 December 2017 / Accepted: 2 January 2018 / Published: 7 January 2018
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Abstract

Scientific workflow applications are collections of several structured activities and fine-grained computational tasks. Scientific workflow scheduling in cloud computing is a challenging research topic due to its distinctive features. In cloud environments, it has become critical to perform efficient task scheduling resulting in reduced scheduling overhead, minimized cost and maximized resource utilization while still meeting the user-specified overall deadline. This paper proposes a strategy, Dynamic Scheduling of Bag of Tasks based workflows (DSB), for scheduling scientific workflows with the aim to minimize financial cost of leasing Virtual Machines (VMs) under a user-defined deadline constraint. The proposed model groups the workflow into Bag of Tasks (BoTs) based on data dependency and priority constraints and thereafter optimizes the allocation and scheduling of BoTs on elastic, heterogeneous and dynamically provisioned cloud resources called VMs in order to attain the proposed method’s objectives. The proposed approach considers pay-as-you-go Infrastructure as a Service (IaaS) clouds having inherent features such as elasticity, abundance, heterogeneity and VM provisioning delays. A trace-based simulation using benchmark scientific workflows representing real world applications, demonstrates a significant reduction in workflow computation cost while the workflow deadline is met. The results validate that the proposed model produces better success rates to meet deadlines and cost efficiencies in comparison to adapted state-of-the-art algorithms for similar problems. View Full-Text
Keywords: IaaS cloud; scientific workflow; resource provisioning; scheduling; cost minimization; deadline-constrained IaaS cloud; scientific workflow; resource provisioning; scheduling; cost minimization; deadline-constrained
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Anwar, N.; Deng, H. Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments. Future Internet 2018, 10, 5.

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