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

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

PLOS ONE, 2021, vol. 16, issue 6, 1-22

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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0252756

DOI: 10.1371/journal.pone.0252756

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