Satisfying real-time requirements in cyber-physical systems is challenging as timing behaviour depends on the application software, the embedded hardware, as well as the execution environment. This challenge is exacerbated as real-world, industrial systems often use unpredictable hardware and software libraries or operating systems with timing hazards and proprietary device drivers. All these issues limit or entirely prevent the application of established real-time analysis techniques. In this paper we propose PReGO, a generative methodology for satisfying real-time requirements in industrial commercial-off-the-shelf (COTS) systems. We report on our experience in applying PReGO to a use-case: A Search and Rescue application running on a fixed-wing drone with COTS components, including an NVIDIA Jetson board and a stock Ubuntu/Linux. We empirically evaluate the impact of each integration step and demonstrate the effectiveness of our methodology in meeting real-time application requirements in terms of deadline misses and energy consumption.
CITATION STYLE
Rouxel, B., Schultz, U. P., Akesson, B., Holst, J., Jørgensen, O., & Grelck, C. (2020). PReGO: A generative methodology for satisfying real-time requirements on COTS-based systems: Definition and experience report. In GPCE 2020 - Proceedings of the 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, Co-located with SPLASH 2020 (pp. 70–83). Association for Computing Machinery, Inc. https://doi.org/10.1145/3425898.3426954
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