Optimization in Heterogeneous Distributed Real-Time Systems based on Partitioning
In this work, a solution that can be applied to the RTSS 2022’s Industry Challenge is proposed. It relies on a real-time system model and a set of schedulability analysis and optimization tools, enabling the design of safety-critical applications compliant with timing requirements. The presented too...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/29141 |
| Acceso en línea: | https://hdl.handle.net/10902/29141 |
| Access Level: | acceso abierto |
| Palabra clave: | MAST Schedulability analysis Optimization Partitioning |
| Sumario: | In this work, a solution that can be applied to the RTSS 2022’s Industry Challenge is proposed. It relies on a real-time system model and a set of schedulability analysis and optimization tools, enabling the design of safety-critical applications compliant with timing requirements. The presented toolchain is enhanced with a novel task allocation technique, which leverages sensitivity analysis and that can be applied to heterogeneous systems, to provide promising solutions that improve state-of-the-art algorithms’ performance. |
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