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Energy-aware workflow scheduling in fog computing using a hybrid chaotic algorithm

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Abstract

Fog computing paradigm attempts to provide diverse processing at the edge of IoT networks. Energy usage being one of the important elements that may have a direct influence on the performance of fog environment. Effective scheduling systems, in which activities are mapped on the greatest feasible resources to meet various competing priorities, can reduce energy use. Consequently, a hybrid discrete optimization method called HDSOS-GOA, which uses the Dynamic voltage and frequency scaling (DVFS) approach, is proposed to handle scientific workflow scheduling challenges in the fog computing environment. HDSOS-GOA combines the search qualities of Symbiotic Organisms Search (SOS) and the Grasshopper Optimization Algorithm (GOA) algorithms and the selection of these algorithms for performing workflow scheduling is based on the probability calculated by the learning automata. The HEFT method is used to determine the task sequence. Our solution focuses on reducing the energy consumption of the scheduling process by reducing the number of Virtual Machines required for workflow execution in addition to optimizing the makespan. Comprehensive experiments are carried out on four different scientific workflows with different sizes with and without deadline constraints to evaluate the performance of the suggested scheduling strategy. The results of the experiments show that scheduling with the suggested approach outperforms other well-known metaheuristic algorithms.

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Data availability

Data generated during the current study are available from the corresponding author upon reasonable request.

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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Computer Engineering, Shahindezh Branch, Islamic Azad University, Shahindezh, Iran

    Ali Mohammadzadeh

  2. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Mahdi Akbari Zarkesh

  3. Department of Computer Engineering, Hashtgerd Branch, Islamic Azad University, Hashtgerd, Iran

    Pouria Haji Shahmohamd

  4. Mechanical Engineering Department, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, USA

    Javid Akhavan

  5. Department of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, 143005, India

    Amit Chhabra

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  1. Ali Mohammadzadeh
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  2. Mahdi Akbari Zarkesh
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Contributions

AM, MAZ, PHS, JA, and Amit Chhabra contributed to the design and implementation of the research, to the analysis of the results and the writing of the manuscript. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Ali Mohammadzadeh.

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Mohammadzadeh, A., Akbari Zarkesh, M., Haji Shahmohamd, P. et al. Energy-aware workflow scheduling in fog computing using a hybrid chaotic algorithm. J Supercomput 79, 18569–18604 (2023). https://doi.org/10.1007/s11227-023-05330-z

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