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Efficient bi-level multi objective approach for budget-constrained dynamic Bag-of-Tasks scheduling problem in heterogeneous multi-cloud environment

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Abstract

Bag-of-Tasks is a well-known model that processes big-data applications supporting embarrassingly parallel jobs with independent tasks. Scheduling Bag-of-Tasks in a dynamic multi-cloud environment is an NP-hard problem that has attracted a lot of attention in the last years. Such a problem can be modeled using a bi-level optimization framework due to its hierarchical scheme. Motivated by this issue, in this paper, an efficient bi-level multi-follower algorithm, based on hybrid metaheuristics, is proposed to solve the multi-objective budget-constrained dynamic Bag-of-Tasks scheduling problem in a heterogeneous multi-cloud environment. In our proposed model, the objective function differs depending on the scheduling level: The upper level aims to minimize the makespan of the whole Bag-of-Tasks under budget constraints; while each follower aims to minimize the makespan and the execution cost of tasks belonging to the Bag-of-Tasks. Since multiple conflicting objectives exist in the lower level, we propose an improved variant of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) called Efficient NSGA-II (E-NSGA-II), applying a recently proposed quick non-dominated sorting algorithm (QNDSA) with quasi-linear average time complexity. By performing experiments on proposed synthetic datasets, our algorithm demonstrates high performance in terms of makespan and execution cost while respecting budget constraints. Statistical analysis validates the outperformance of our proposal regarding the considering metrics.

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Data Availability

The datasets generated during the current study are available at the following link: https://github.com/MounaKaraja/Dynamic-BoT-Scheduling-Problem-in-multi-cloud-environment. Further informations are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. SMART Lab, ISG Computer Science Department, University of Tunis, Tunis, Tunisia

    Mouna Karaja, Abir Chaabani, Ameni Azzouz & Lamjed Ben Said

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  1. Mouna Karaja
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  2. Abir Chaabani
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  4. Lamjed Ben Said
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Karaja, M., Chaabani, A., Azzouz, A. et al. Efficient bi-level multi objective approach for budget-constrained dynamic Bag-of-Tasks scheduling problem in heterogeneous multi-cloud environment. Appl Intell 53, 9009–9037 (2023). https://doi.org/10.1007/s10489-022-03942-1

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