期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 6, 页码 4219-4228出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.2995348
关键词
Cloud computing; Task analysis; Dynamic scheduling; Job shop scheduling; Security; Real-time systems; Cloud-based industrial applications; dynamic scheduling; particle swarm optimization (PSO); real-time optimization; security
类别
资金
- National Natural Science Foundation of China [61702264, 61872219]
- Fundamental Research Funds for the Central Universities [30918014108]
- Postdoctoral Science Foundation of China [2019M651835]
- Natural Science Foundation of Shandong Province [ZR2019MF001, TII-20-0744]
This article proposes a security-aware dynamic scheduling method for real-time resource allocation in ICS. A three-level security model is designed for tasks and cloud resources in ICS, and a two-tier heterogeneous cloud architecture is introduced. A security-aware scheduling method based on distributed particle swarm optimization is presented for resource allocation, with a dynamic scheduling mechanism based on dynamic workflow model to address the dynamics of edge resources and mobile industrial applications.
Nowadays, large number of cloud-based techniques have been used in industrial control systems (ICS), which also brings many security threats. The emergence of security-aware industrial control has paved the way of security-aware scheduling in cloud-based industrial applications. Actually, most cloud-based industrial applications are time sensitive, which need real-time processing. Edge cloud computing paradigm extends the computing ability of traditional cloud model with low-latency local resources. Thus, heterogeneous clouds that consist of both centralized resources and edge resources may be a promising resource model to provide both scalable and low-latency resources for cloud-based industrial applications. In view of these challenges, in this article, we propose a security-aware dynamic scheduling method for real-time resource allocation in ICS. First, a three-level security model is designed for both tasks and cloud resources in ICS, and a two-tier heterogeneous cloud architecture is introduced. Accordingly, a security-aware scheduling method based on distributed particle swarm optimization is presented for resource allocation with security concerns. To deal with the dynamics of edge resources and the mobility of mobile industrial applications, a dynamic scheduling mechanism based on dynamic workflow model is proposed for real-time optimization. Experimental results validate that the scheduling control policy proposed in this article can achieve a good balance between scheduling performance and security performance.
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