PReGO: a generative methodology for satisfying real-time requirements on COTS-based systems definition and experience report
| Authors |
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|---|---|
| Publication date | 2020 |
| Host editors |
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| Book title | GPCE '20 |
| Book subtitle | proceedings of the 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences : November 16-17, 2020, Virtual, USA |
| ISBN (electronic) |
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| Event | 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences |
| Pages (from-to) | 70-83 |
| Number of pages | 14 |
| Publisher | New York, NY: Association for Computing Machinery |
| Organisations |
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| Abstract |
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 & 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.
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| Document type | Conference contribution |
| Note | With supplemental material. |
| Language | English |
| Published at | https://doi.org/10.1145/3425898.3426954 |
| Published at | https://www.akesson.nl/files/pdf/rouxel20-gpce.pdf |
| Downloads |
rouxel20-gpce
(Accepted author manuscript)
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