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Budget-based resource provisioning and scheduling algorithm for scientific workflows on IaaS cloud

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Abstract

The deployment of cloud computing, specifically Infrastructure as a Service (IaaS) clouds, have become an interested topic in recent years for the execution of compute-intensive scientific workflows. These platforms deliver on-demand connectivity to those infrastructure needed for workflow execution, providing customers to pay only for the service they utilize. As a result schedulers are forced to meet a quid-pro-quo among two main QoS criteria: cost and time. The maximum of this research work has been on making scheduling algorithms with the goal of reducing infrastructure costs as fulfilling a user-specified deadline. Few algorithms, on the other hand, have considered the problem of reducing workflow execution time while staying within a budget. This work consider on the latter scenario. We offer a Budget-based resource Provisioning and Scheduling (BPS) algorithm for scientific workflows used in IaaS service. This proposal was developed to face challenges specifically to clouds like resource performance variation, resource heterogeneity, infinite on-demand connectivity, and pay-as-you-go type (i.e. per-minute pricing). It is efficient of responding to the cloud dynamics, and is powerful in creating suitable solutions that fulfill a user-specified budget and reduce the makespan of the leveraged environment. At last, the experimental events confirms that it runs a workflow efficiently with respect to achieving budget of 94% and minimizing makespan of 29% than the state-of-the-art budget-aware algorithms.

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Data availability

The data that support the findings of this study are available from the corresponding author [Rajasekar p], upon reasonable request.

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  1. Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India

    Rajasekar P & Santhiya P

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  1. Rajasekar P
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Rajasekar P contributed to technical, conceptual and mathematical model (Unbounded Knapsack Problem) of this paper, and Santhiya P contributed to guidance and counselling on writing of this paper.

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Correspondence to Rajasekar P.

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P, R., P, S. Budget-based resource provisioning and scheduling algorithm for scientific workflows on IaaS cloud. Multimed Tools Appl 83, 50981–51007 (2024). https://doi.org/10.1007/s11042-023-17549-2

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