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An energy-efficient and deadline-aware workflow scheduling algorithm in the fog and cloud environment

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Abstract

The Internet of Things (IoT) is constantly evolving. The variety of IoT applications has caused new demands to emerge on users’ part and competition between computing service providers. On the one hand, an IoT application may exhibit several important criteria, such as deadline and runtime simultaneously, and it is confronted with resource limitations and high energy consumption on the other hand. This has turned to adopting a computing environment and scheduling as a fundamental challenge. To resolve the issue, IoT applications are considered in this paper as a workflow composed of a series of interdependent tasks. The tasks in the same workflow (at the same level) are subject to priorities and deadlines for execution, making the problem far more complex and closer to the real world. In this paper, a hybrid Particle Swarm Optimization and Simulated Annealing algorithm (PSO–SA) is used for prioritizing tasks and improving fitness function. Our proposed method managed the task allocation and optimized energy consumption and makespan at the fog-cloud environment nodes. The simulation results indicated that the PSO–SA enhanced energy and makespan by 5% and 9% respectively on average compared with the baseline algorithm (IKH-EFT).

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Data availability

The dataset used and analyzed during the current study is available from the corresponding author upon reasonable request.

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Funding

No funding was obtained this study.

Author information

Authors and Affiliations

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

    Navid Khaledian & Keyhan Khamforoosh

  2. Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran

    Reza Akraminejad

  3. Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, 19328, Jordan

    Laith Abualigah

  4. Department of Computer Science and Engineering, Korea University, Seoul, 02841, Republic of Korea

    Danial Javaheri

  5. Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Navid Khaledian

Authors
  1. Navid Khaledian
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  2. Keyhan Khamforoosh
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  4. Laith Abualigah
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  5. Danial Javaheri
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Contributions

NK: Conceptualization, methodology, writing—original draft preparation. KK: Supervising, Data curation, writing—reviewing and editing, validation. RA: Software, visualization, investigation. LA: Writing—reviewing and editing, validation. DJ: Writing—reviewing and editing.

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Correspondence to Navid Khaledian.

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Khaledian, N., Khamforoosh, K., Akraminejad, R. et al. An energy-efficient and deadline-aware workflow scheduling algorithm in the fog and cloud environment. Computing 106, 109–137 (2024). https://doi.org/10.1007/s00607-023-01215-4

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  • DOI: https://doi.org/10.1007/s00607-023-01215-4

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