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Adaptive Computing Optimization in Software-Defined Network-Based Industrial Internet of Things with Fog Computing.

Juan Wang1, Di Li2

  • 1School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China. wjhao456@163.com.

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Summary
This summary is machine-generated.

This study proposes a method for smart factories to select optimal computing modes (local, fog, or cloud) and task execution sequences. The approach enhances real-time performance and reliability in Industrial Internet of Things systems.

Keywords:
IIoTcomputing mode selection (CMS)fog computingsoftware-defined network (SDN)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Industrial Engineering

Background:

  • Cloud and fog computing offer enhanced local computing capabilities for devices.
  • Offloading tasks to fog or cloud servers significantly reduces processing time.
  • Fog servers deployed at the network edge are crucial for Quality of Service (QoS) in smart manufacturing.

Purpose of the Study:

  • To determine the optimal computing mode (local, fog, or cloud) for tasks in a mixed computing system.
  • To define the execution sequence for tasks in a fog computing mode based on priority.
  • To improve the efficiency and reliability of Industrial Internet of Things (IIoT) systems in smart factories.

Main Methods:

  • Design of a Software-Defined Network (SDN) framework for smart factories within an IIoT system.
  • Development of a Computing Mode Selection (CMS) module within the SDN controller.
  • Implementation of an algorithm for execution sequences based on task priority (ASTP), prioritizing tasks with higher real-time needs and computational load.

Main Results:

  • The CMS module successfully assigns an optimal computing mode to each task.
  • Task priorities are calculated based on real-time performance requirements and computational complexity.
  • SDN controller utilizes task priorities to manage task transmission, ensuring higher priority tasks receive fog computing services earlier.

Conclusions:

  • The proposed method effectively optimizes computing mode selection and task execution sequencing.
  • The SDN-based framework enhances real-time performance and reliability in Industrial Internet of Things environments.
  • This approach contributes to the advancement of smart manufacturing systems through efficient resource management.