Industrial control systems are applied in many areas e.g., motion control for industrial robotics, process control of large plants such as in the area of oil and gas, and in large national power grids. Since the last decade with advancement and adoption of virtualization and multicore technology (e.g., Virtual Monitoring Machine, cloud computing, server virtualization, application virtualization), IT systems, automation industries have benefited from low investment, effective system management and high service availability. However, virtualization and multicore technologies have posed a serious challenge to real-time systems, which is violating timeliness and predictability of real-time application running on control systems. To address the challenge, we have extended a real-time component-based framework with virtual nodes; and evaluated the framework in the context of virtualized multicore environment. The evaluation is demonstrated by modeling and implementing an orchestra application with QoS for CPU, memory and network bandwidth. The orchestra application is a real-time and distributed application deployed on virtualized multicore PCs connected with speakers. The result shows undistorted orchestra performance played through speakers connected to physical computer nodes. The contribution of the thesis can be considered: 1) extending a real-time component-based framework, Future Automation Software Architecture (FASA) with virtual nodes using Virtual Computation Resource (VCR) and 2) design and installation of reusable test environment for development, debugging and testing of real-time application on a network of virtualized multicore environment. ; Vinnova project “AUTOSAR for Multi-Core in Automotive and Automation Industries “


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    Title :

    Automated Orchestra for Industrial Automation on Virtualized Multicore Environment ; Extending Real-Time component-based Framework to Virtual Nodes : Demonstration: Automated Orchestra real-time Application


    Contributors:

    Publication date :

    2013-01-01


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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