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A cost and makespan aware scheduling algorithm for dynamic multi-workflow in cloud environment

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Abstract

With the development of cloud computing, a growing number of workflows are deployed on cloud platform that can dynamically provides cloud resources on demand for users. In clouds, one basic problem is how to schedule workflow for minimizing the execution cost and the workflow completion time. Aiming at the problem that the maximum completion time and cost of multiple workflows are too high, this paper proposes a model of dynamic multi-workflow scheduling in cloud environment and a new scheduling algorithm which is named as MT (multi-workflow scheduling technology). In MT, the heterogeneity of resources is considered when calculating the priority of tasks. Then, the technique for order of preference by similarity to ideal solution (TOPSIS) method is used to rank the resources when selecting resources for tasks. Finally, MT takes the estimated minimum completion time of the workflow and the cost of the task as two attribute indexes in TOPSIS decision matrix. Also, it uses a fixed reference point instead of calculating ideal solution, which ensures the uniqueness of the evaluation criteria when there is a change in the number of resources. Simulation experiments are illustrated to verify the effectiveness of the proposed algorithm in reducing the maximum completion time and cost of multiple workflows. Compared with the state-of-the-art methods, the maximum completion time and cost can be reduced by at most 17 and \(9\%\), respectively.

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Notes

  1. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, it is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution and the longest geometric distance from the negative ideal solution [10].

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Acknowledgements

All codes and data are published on GitHub [21]. There is no conflict of interest in this paper.

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Authors and Affiliations

  1. School of Automation, Beijing Institute of Technology, Beijing, 100081, China

    Yuanqing Xia, Yufeng Zhan, Li Dai & Yuehong Chen

  2. Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314000, China

    Yufeng Zhan

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  1. Yuanqing Xia
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  2. Yufeng Zhan
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Correspondence to Yufeng Zhan.

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Xia, Y., Zhan, Y., Dai, L. et al. A cost and makespan aware scheduling algorithm for dynamic multi-workflow in cloud environment. J Supercomput 79, 1814–1833 (2023). https://doi.org/10.1007/s11227-022-04681-3

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