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Multi-objective approach for scheduling time-aware business processes in cloud-fog environment

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A Correction to this article was published on 02 December 2022

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Abstract

Currently, constant innovations in service-oriented architectures lead to extending the Cloud services with promising solutions such as Fog computing. As the Cloud-Fog environment still remains in its infancy stage, several issues remain among the considerable challenges to be handled. One of the key issues in a Cloud-Fog environment is the scheduling of business processes tasks, i. e. selecting the suitable Cloud-Fog resources to support the execution of the business processes tasks while considering budget and temporal constraints. Indeed, these constraints are generally contradictory. Indeed, the use of cheaper resources increases the execution time and vice versa. Furthermore, minimizing the energy consumption is among the prominent considerations when dealing with Cloud-Fog environment. Hence, finding out the trade-off set of optimal solutions is required considering minimizing cost, time and energy consumption. To address such an issue, we propose, in this paper, a Multi-Objectives Particle Swarm Optimization (MOPSO) algorithm based on a non-dominance sort to handle the scheduling problem of time-aware business processes with many conflicting objective functions. Our algorithm aims to optimize three conflicting objectives namely, the makespan (total execution time), the monetary cost and the energy consumption while taking into account budget and temporal constraints of the business process. The output of our MOPSO algorithm represents a set of Pareto optimal solutions from which the user can select the best one. The elaborated experimentation illustrates the good performance of the proposed algorithm.

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Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Notes

  1. https://www.engadget.com/2016/12/14/amazon-completes-its-first-drone-powered-delivery/.

  2. The datasets used during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2022R125), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

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Authors and Affiliations

  1. ReDCAD, ENIS, University of Sfax, Sfax, Tunisia

    Fairouz Fakhfakh & Saoussen Cheikhrouhou

  2. ISMAIK, University of Kairaoun, Kairaoun, Tunisia

    Fairouz Fakhfakh

  3. Department of Computer Science and Information Technology, Applied college, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

    Bouthaina Dammak

  4. Information Technology Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

    Monia Hamdi

  5. MIRACL, ISIMS, University of Sfax, Sfax, Tunisia

    Mouna Rekik

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Correspondence to Bouthaina Dammak.

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“The original online version of this article was revised:” Fairouz Fakhfakh was incorrectly denoted as the corresponding author, but it should have been Bouthaina Dammak.

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Fakhfakh, F., Cheikhrouhou, S., Dammak, B. et al. Multi-objective approach for scheduling time-aware business processes in cloud-fog environment. J Supercomput 79, 8153–8177 (2023). https://doi.org/10.1007/s11227-022-04690-2

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