Xiaomin Li, Jiafu Wan, Hong-Ning Dai, Muhammad Imran, Min Xia, Antonio Celesti
IEEE Transactions on Industrial Informatics, vol. 15, no. 7, pp. 4225-4234, July 2019
Publication year: 2019


At present, smart manufacturing computing framework has faced many challenges such as the lack of an effective framework of fusing computing historical heritages and resource scheduling strategy to guarantee the low latency requirement. In this paper, we propose a hybrid computing framework and design an intelligent resource scheduling strategy to fulfill the real-time requirement in smart manufacturing with edge computing support. First, a four-layer computing system in a smart manufacturing environment is provided to support the AI task operation with the network perspective. Then, a two-phase algorithm for scheduling the computing resources in the edge layer is designed based on greedy and threshold strategies with latency constraints. Finally, a prototype platform was developed. We conducted experiments on the prototype to evaluate the performance of the proposed framework with a comparison of the traditionally-used methods. The proposed strategies have demonstrated the excellent real-time, satisfaction degree and energy consumption performance of computing services in smart manufacturing with edge computing.


  • Industry 4.0
  • Smart Manufacturing
  • Edge Computing
  • Resource Scheduling


	author={Xiaomin Li and Jiafu Wan and Hong-Ning Dai and Muhammad Imran and Min Xia and Antonio Celesti}, 
	journal={IEEE Transactions on Industrial Informatics}, 
	title={A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing}, 
	pages={4225 - 4234}, 

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