Next Article in Journal
Flood Hazard Assessment of the Urban Area of Tabuk City, Kingdom of Saudi Arabia by Integrating Spatial-Based Hydrologic and Hydrodynamic Modeling
Next Article in Special Issue
Energy-Efficient Collaborative Task Computation Offloading in Cloud-Assisted Edge Computing for IoT Sensors
Previous Article in Journal
Erratum: Wang, P., et al. Monitoring of the Pesticide Droplet Deposition with a Novel Capacitance Sensor. Sensors 2019, 19, 537
Previous Article in Special Issue
Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach
Article Menu
Issue 5 (March-1) cover image

Export Article

Open AccessArticle

Task Scheduling Based on a Hybrid Heuristic Algorithm for Smart Production Line with Fog Computing

School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(5), 1023; https://doi.org/10.3390/s19051023
Received: 15 January 2019 / Revised: 10 February 2019 / Accepted: 21 February 2019 / Published: 28 February 2019
(This article belongs to the Special Issue Recent Advances in Fog/Edge Computing in Internet of Things)
  |  
PDF [2623 KB, uploaded 28 February 2019]
  |     |  

Abstract

Fog computing provides computation, storage and network services for smart manufacturing. However, in a smart factory, the task requests, terminal devices and fog nodes have very strong heterogeneity, such as the different task characteristics of terminal equipment: fault detection tasks have high real-time demands; production scheduling tasks require a large amount of calculation; inventory management tasks require a vast amount of storage space, and so on. In addition, the fog nodes have different processing abilities, such that strong fog nodes with considerable computing resources can help terminal equipment to complete the complex task processing, such as manufacturing inspection, fault detection, state analysis of devices, and so on. In this setting, a new problem has appeared, that is, determining how to perform task scheduling among the different fog nodes to minimize the delay and energy consumption as well as improve the smart manufacturing performance metrics, such as production efficiency, product quality and equipment utilization rate. Therefore, this paper studies the task scheduling strategy in the fog computing scenario. A task scheduling strategy based on a hybrid heuristic (HH) algorithm is proposed that mainly solves the problem of terminal devices with limited computing resources and high energy consumption and makes the scheme feasible for real-time and efficient processing tasks of terminal devices. Finally, the experimental results show that the proposed strategy achieves superior performance compared to other strategies. View Full-Text
Keywords: fog computing; task scheduling; smart manufacturing; hybrid heuristic (HH) algorithm fog computing; task scheduling; smart manufacturing; hybrid heuristic (HH) algorithm
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wang, J.; Li, D. Task Scheduling Based on a Hybrid Heuristic Algorithm for Smart Production Line with Fog Computing. Sensors 2019, 19, 1023.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top