Title: Computing modes-based task processing for industrial internet of things

Authors: Juan Wang; Jinchao Xiao; Di Li

Addresses: School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, Guangdong Province, China ' Shenyang Institute of Automation, Guangzhou, Chinese Academy of Sciences, Guangzhou 511458, Guangdong Province, China ' School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, Guangdong Province, China

Abstract: The industrial internet of things (IIoT) is facing enormous challenges, including limited computing resources and network bandwidth and high energy consumption. To facilitate the realisation of IIoT-enabled manufacturing, several problems concerning computing modes and interaction patterns among fog nodes and the cloud should be clarified: what the typical computing modes are; what their advantages and drawbacks are; and how the tasks are calculated in different computing modes. The above-listed problems are the focus of this paper. Four computing modes are listed accordingly, namely, local computing, remote computing, cloud computing and fog computing. The system model is established for each kind of computing mode, and the models for delay and energy consumption are formulated. A task processing experiment platform is setup in simulation software. The experimental results show that compared with other computing modes, fog computing exhibits better performance in terms of delay and energy consumption.

Keywords: industrial internet of things; IIoT; task processing; cloud computing; fog computing.

DOI: 10.1504/IJAACS.2019.103673

International Journal of Autonomous and Adaptive Communications Systems, 2019 Vol.12 No.4, pp.343 - 357

Received: 31 May 2018
Accepted: 04 Oct 2018
Published online: 20 Nov 2019 *

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