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Efficient energy and completion time for dependent task computation offloading algorithm in industry 4.0

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  • Rabab Farouk Abdel-Kader
  • Noha Emad El-Sayad
  • Rawya Yehia Rizk

Abstract

Rapid technological development has revolutionized the industrial sector. Internet of Things (IoT) started to appear in many fields, such as health care and smart cities. A few years later, IoT was supported by industry, leading to what is called Industry 4.0. In this paper, a cloud-assisted fog-networking architecture is implemented in an IoT environment with a three-layer network. An efficient energy and completion time for dependent task computation offloading (ET-DTCO) algorithm is proposed, and it considers two quality-of-service (QoS) parameters: efficient energy and completion time offloading for dependent tasks in Industry 4.0. The proposed solution employs the Firefly algorithm to optimize the process of the selection-offloading computing mode and determine the optimal solution for performing tasks locally or offloaded to a fog or cloud considering the task dependency. Moreover, the proposed algorithm is compared with existing techniques. Simulation results proved that the proposed ET-DTCO algorithm outperforms other offloading algorithms in minimizing energy consumption and completion time while enhancing the overall efficiency of the system.

Suggested Citation

  • Rabab Farouk Abdel-Kader & Noha Emad El-Sayad & Rawya Yehia Rizk, 2021. "Efficient energy and completion time for dependent task computation offloading algorithm in industry 4.0," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-22, June.
    • Handle: RePEc:plo:pone00:0252756
    DOI: 10.1371/journal.pone.0252756
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    References listed on IDEAS

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    1. Lina Zhang & Liqiang Liu & Xin-She Yang & Yuntao Dai, 2016. "A Novel Hybrid Firefly Algorithm for Global Optimization," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
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    Cited by:

    1. Javid Misirli & Emiliano Casalicchio, 2023. "An Analysis of Methods and Metrics for Task Scheduling in Fog Computing," Future Internet, MDPI, vol. 16(1), pages 1-22, December.

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