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研究生： Gabor Szolnok
Gábor Szolnok
論文名稱： Human-Aware Edge Computing Scheduling for Cyber-Physical Systems
Human-Aware Edge Computing Scheduling for Cyber-Physical Systems
指導教授： 王超
Chao Wang
Didem Gurdur Broo
Didem Gurdur Broo
口試委員： 王超
Chao Wang
Didem Grudur Broo
Didem Grudur Broo
Mats Daniels
Mats Daniels
口試日期： 2024/06/26
學位類別： 碩士
Master
系所名稱： 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年： 2024
畢業學年度： 112
語文別： 英文
論文頁數： 59
英文關鍵詞： Cyber-Physical Systems, Edge Computing, HiLCPS, scheduling
研究方法: 實驗設計法 、 個案研究法
DOI URL： http://doi.org/10.6345/NTNU202401331
論文種類： 學術論文
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    This work delves into the realm of cyber-physical systems (CPS), focusing on their integration within factory environments, where human actuators are also responsible for performing tasks in the physical world as parts of the process.

    CPS involves the fusion of computer-based algorithms and physical processes, wherein computations and physical actions mutually influence each other. However, the computational demands of monitoring and control in CPS can challenge centralized systems due to potential data overload. Edge computing emerges as a promising solution, allowing data processing closer to edge devices and facilitating workload distribution among nodes.

    Incorporating humans into CPS, termed Human-in-the-Loop (HiL) tasks, demands a careful design to avoid potential accidents. Furthermore, human factors introduce unpredictability, posing challenges such as variable response times.

    I began by introducing fundamental concepts widely utilized in CPS and task scheduling and described the fundamental ideas behind edge computing. I designed and implemented a CPS environment that simulated a factory production scenario. Through a literature study, I investigated the integration of edge computing into CPS and explored various scheduling techniques at both the kernel and application levels. The objective was to mitigate latency and enhance the speed of Human-in-the-Loop callback chains. Lastly, I integrated the insights gleaned from the literature study into the simulated environment to validate the findings and identify potential areas for improvement.

    1. Introduction [1] 1.1 Research questions [2] 2. Background [3] 2.1 Cyber Physical Systems (CPS) [3] 2.1.1 Feedback control [4] 2.1.2 Human in the loop [4] 2.1.3 Designing HiLCPS collaboration [6] 2.2 Edge computing [7] 2.2.1 Edge Computing Architectures [7] 2.3 Scheduling algorithms [9] 2.3.1 Task types [10] 2.3.1 Task states [10] 2.3.1 Constraints [11] 2.3.1 Classification of the scheduling algorithms [13] 2.4 Kernel and application level scheduling [13] 2.5 Robot Operating System 2 [16] 2.5.1 Architecture description [16] 2.5.2 Scheduling tools [17] 3. Methodology [19] 4. Literature review [20] 4.1 Scheduling decisions [20] 4.1.1 Observations about the scheduling technique of ROS2 [20] 4.1.2 OS and application scheduler interaction [22] 4.2 HiLCPS in factory environments [22] 4.3 Edge computing in CPS [24] 5. Implementation: Spinning CPS for industrial mass production [25] 5.1 Scenario description [26] 5.1.1 Simplifications [28] 5.2 System architecture [28] 5.2.1 Camera driver [29] 5.2.2 MyCobot driver [31] 5.2.3 Human-in-the-Loop driver [32] 5.2.4 Controller [33] 5.3 Tasks [35] 5.4 HiL tasks within the system [36] 6. Experiments [39] 6.1 OS level scheduling [39] 6.2 Optimizing the human interaction capture [41] 6.2.1 Improving the execution speed of the camera drivers [41] 6.2.2 Communication between the camera drivers and the receivers [45] 6.3 Scheduling HiL tasks [47] 7. Discussion [49] 7.1 What is the holistic approach to design scheduling strategies for cyber-physical systems when human collaboration is involved? [49] 7.2 How can schedulers be enhanced to better accommodate the dynamic nature of human-machine interaction considering factors such as varying response time? [51] 7.3 What are the different scenarios in which edge computing is necessary and beneficial for CPS human collaboration? [52] 7.4 What is the most suitable edge computing architecture to address these scenarios? [53] 8. Conclusion, Future works [55]

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