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Caching-based task scheduling for edge computing in intelligent manufacturing

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Abstract

Tasks have high requirements for response delay and security in intelligent manufacturing. Industrial data have the characteristics of high privacy. However, cloud services are difficult to implement for low latency-sensitive applications and privacy data tasks. Therefore, the offloading technology in edge computing can offload the computing tasks of terminal devices to the edge of the network, which can effectively reduce the delay and match the needs of intelligent manufacturing. Unreasonable task scheduling cannot meet the needs of real-time scheduling between edge servers and cloud servers. In this paper, we establish a joint low-delay optimization model of task scheduling and dynamic replacement-release caching (DRRC) mechanism, which couples a privacy selection strategy for tasks to protect privacy. Tasks are scheduled to different location by the privacy of sensitive data, which can improve the security of data and meet the calculation request of different tasks. DRRC mechanism caches tasks according to the size of the task and replaces it with the weight of the task data, and adds automatic release mechanism. To solve the task scheduling strategy, we design the improved genetic-differential evolution algorithm. Extensive simulations reveal that the proposed algorithm has a better performance in minimizing latency compared with other scheduling algorithms. At the same time, the caching mechanism has a better hit rate.

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Acknowledgements

This work was supported by the Natural Science Basic Research Program of Shaanxi (Program No. 2021JQ-719), the Science and Technology Project of Shaanxi (Program No.2019ZDLGY07-08), the Young Teachers Research Foundation of Xi’an University of Posts and Telecommunications, and the Special Funds for Construction of Key Disciplines in Universities in Shaanxi.

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Authors and Affiliations

  1. School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an, 710121, Shaanxi, China

    Zhongmin Wang, Gang Wang & Xiaomin Jin

  2. Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi’an University of Posts and Telecommunications, Xi’an, 710121, Shaanxi, China

    Zhongmin Wang, Gang Wang & Xiaomin Jin

  3. ZTE Corporation, No.55, Hi-techRoadSouth, Shenzhen, 518057, China

    Xiang Wang & Jianwei Wang

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  1. Zhongmin Wang
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  2. Gang Wang
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Correspondence to Gang Wang.

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Wang, Z., Wang, G., Jin, X. et al. Caching-based task scheduling for edge computing in intelligent manufacturing. J Supercomput 78, 5095–5117 (2022). https://doi.org/10.1007/s11227-021-04071-1

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