4.8 Article

Multiobjective Placement for Secure and Dependable Smart Industrial Environments

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 17, Issue 2, Pages 1298-1306

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.2978771

Keywords

Computational modeling; Security; Hardware; Privacy; Virtualization; Cloud computing; Optimization; Dependability; heuristic; optimization; placement; security and privacy; smart industrial environment

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Cyber-physical systems enable efficient, highly automated, and green smart industrial environments through the critical asset of computation. Suitable placement mechanisms can pursue various security and dependability goals in computing, preventing information leakages, providing redundancy, counteracting hardware outages or software aging, avoiding privacy breaks, and mitigating wastage of resources and energy.
Cyber-physical systems allow to implement efficient, highly automated, and green smart industrial environments. To this aim, computation is a critical asset to control machineries, process data, and run proper optimization strategies. In general, computing capabilities are provided by virtualizing resources of local devices or servers deployed in a remote datacenter. Thus, their management is crucial for the security of the cyber-physical ecosystem or to engineer dependable industrial environments. In this article, we introduce a placement mechanism to pursue various security and dependability goals, such as preventing information leakages, providing redundancy, counteracting hardware outages or software aging, avoiding privacy breaks, and mitigating wastage of resources and energy. Multiobjective placement actions are computed by solving suitable mathematical programming problems with competing objectives. Simulations performed using real workload traces showcase the effectiveness of the approach in comparison with bin-packing-based heuristics.

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