Orchestrated Platform for Cyber-Physical Systems

Orchestrated Platform for Cyber-Physical Systems

One of the main driving forces in the era of cyber-physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data...

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Bibliographic Details
Published in:Complexity (New York, N.Y.) Vol. 2018; no. 2018; pp. 1 - 16
Main Authors: Kádár, Botond, Kovács, József, Ács, Sándor, Marosi, Attila Csaba, Farkas, Attila, Lovas, Róbert, Szalóki, Ádám
Format: Journal Article
Language:English
Published: Cairo, Egypt Hindawi Publishing Corporation 01-01-2018
Hindawi
John Wiley & Sons, Inc
Hindawi Limited
Hindawi-Wiley
Subjects:
Agricultural management
Automation
Cloud computing
Computer science
Computer simulation
Containers
Cyber-physical systems
Discrete event systems
Electrical equipment and supplies industry
Forecasts and trends
International conferences
Manufacturing
Middleware
R&D
Research & development
Sensors
Simulation
Software
Virtual computer systems
Virtual reality
United States
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Summary:One of the main driving forces in the era of cyber-physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the “twin digital model” or virtual factory of the existing physical processes for (among others) predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, a novel software container-based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on-demand for these two typical major pillars of CPS: (1) server-side (i.e., back-end) framework for sensor networks and (2) configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete-event simulation tool and the layered back-end framework starting from simple virtual machine-level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on (among others) the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Occopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform.
ISSN:1076-2787
1099-0526
DOI:10.1155/2018/8281079