| 1. |
- Barzegaran, Mohammadreza, et al.
(författare)
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Electric drives as fog nodes in a fog computing-based industrial use case
- 2021
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Ingår i: The Journal of Engineering. - : WILEY. - 2051-3305. ; 2021:12, s. 745-761
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Tidskriftsartikel (refereegranskat)abstract
- Electric drives, which are a main component in industrial applications, control electric motors and record vital information about their respective industrial processes. The development of electric drives as Fog nodes within a fog computing platform (FCP) leads to new abilities such as programmability, analytics, and connectivity, increasing their value. In this study, the FORA FCP reference architecture is used to implement electric drives as Fog nodes, which is called "fogification". The fogified drive architecture and its components are designed using Architecture Analysis and Design Language (AADL). The design process was driven by the high-level requirements that the authors elicited. Both the fogified drive architecture and the current drive architecture are used to implement a self baggage drop system in which electric drives are the key components. The fog-based design was then evaluated using several key performance indicators (KPIs), which reveal its advantages over the current drive architecture. The evaluation results show that safety-related isolation is enabled with only 9% overhead on the total Fog node utilization, control applications are virtualized with zero input-output jitter, the hardware cost is reduced by 44%, and machine learning at the edge is performed without interrupting the main drive functionalities and with an average 85% accuracy. The conclusion is that the fog-based design can successfully implement the required electric drive functionalities and can also enable innovative uses needed for realizing the vision of Industry 4.0.
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| 2. |
- Barzegaran, Mohammadreza, et al.
(författare)
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Fogification of Electric Drives: An industrial use case
- 2020
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Ingår i: The 25th International Conference on Emerging Technologies and Factory Automation ETFA2020.
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Konferensbidrag (refereegranskat)abstract
- Electric drives are used to control electric motors, which are pervasive in industrial applications. In this paper we propose enhancing the electric drives to fulfil the role of fog nodes within a Fog Computing Platform (FCP). Fog Computing is envisioned as a realization of future distributed architectures in Industry 4.0. We identify the system-level requirements of such an FCP, including requirements that are extracted from the current architecture of drives, which we consider as a baseline. These requirements are then used to design a system-level architecture, which we model using the Architecture Analysis & Design Language (AADL). We identify the “technology bricks” (components such as hardware, software, middleware, services, methods and tools) needed to implement the FCP. The proposed fog-based architecture is then used to implement a Conveyor Belt industrial use case. We evaluate the resulting use case on several aspects, demonstrating the usefulness of the proposed fogbased approach. By developing the electric drives as fog nodes, new offerings like programmability, analytics and connectivity to customer Clouds are expected to increase the added value. Increased flexibility allows drives to assume a larger role in industrial and domestic control systems, instrumenting thus also legacy systems by using drives as the data source.
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| 3. |
- Barzegaran, Mohammadreza, et al.
(författare)
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Performance Optimization of Control Applications on Fog Computing Platforms Using Scheduling and Isolation
- 2020
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Ingår i: IEEE Access. - 2169-3536. ; 8, s. 104085-104098
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we address mixed-criticality applications characterized by their safety criticality and time-dependent performance, which are virtualized on a Fog Computing Platform (FCP). The FCP is implemented as a set of interconnected multicore computing nodes, and brings computation and communication closer to the edge of the network, where the machines are located in industrial applications. We use partitioning and static-cyclic scheduling to provide isolation among mixed-criticality tasks and to guarantee their timing requirements. The temporal and spatial isolation is enforced via partitions, which execute tasks with the same criticality level. We consider that the tasks are scheduled using static cyclic scheduling. We are interested in determining the mapping of tasks to the cores of the fog nodes, the assignment of tasks to the partitions, the partition schedule tables, and the tasks’ schedule tables, such that the Quality-of-Control for the control tasks is maximized and we meet the timing requirements for all tasks, including tasks with lower-criticality levels. We are also interested in determining the periods for control tasks to balance the schedulability and the control performance. We have proposed a Simulated Annealing metaheuristic, which relies on a heuristic algorithm for determining the schedules and partitions, to solve this optimization problem. Our optimization strategy has been evaluated on several test cases, showing the effectiveness of the proposed method.
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| 4. |
- Barzegaran, Mohammadreza, et al.
(författare)
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Towards quality-of-control-aware scheduling of industrial applications on fog computing platforms
- 2019
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Ingår i: IoT-Fog 2019 - Proceedings of the 2019 Workshop on Fog Computing and the IoT. - New York, NY, USA : ACM. - 9781450366984 ; , s. 1-5
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Konferensbidrag (refereegranskat)abstract
- In this paper we address Industrial IoT control applications which are safety-critical and real-time, and which have very low latency and jitter requirements. These control applications are virtualized as software tasks running on a Fog Computing Platform that brings computing and deterministic communication closer to the edge of the network, where the industrial "things" are located. Due to the demanding dependability and timing requirements, we consider that the tasks are scheduled with a static-cyclic scheduling policy. We are interested to determine the mapping of the tasks and a schedule table of their activation, such that we maximize the quality-of-control for the control tasks and meet the timing requirements for all tasks, including non-critical real-time tasks. We have proposed a Simulated Annealing-based metaheuristic to solve this problem, and we have evaluated the solution on several test cases.
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| 5. |
- Cervin, Anton, et al.
(författare)
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Using JitterTime to Analyze Transient Performance in Adaptive and Reconfigurable Control Systems
- 2019
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Ingår i: 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). - 9781728103037 - 9781728103020 - 9781728103044
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Konferensbidrag (refereegranskat)abstract
- This paper presents JitterTime, a small Matlab toolbox for calculating the transient performance of a control system in non-ideal timing scenarios. Such scenarios arise in networked and embedded systems, where several applications share a set of limited and varying resources. Technically, the toolbox evaluates the time-varying state covariance of a mixed continuous/discrete linear system driven by white noise. It also integrates a quadratic cost function for the system. The passing of time and the updating of the discrete-time systems are explicitly managed by the user in a simulation run. Since the timing is completely handled by the user, any complex timing scenario can be analyzed, including adaptive scheduling and reconfiguration between different system modes. Three examples of how the toolbox can be used to evaluate the control performance of such time-varying systems are given.
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