Towards Real-Time Aggregate Computing
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| Názov: | Towards Real-Time Aggregate Computing |
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| Autori: | Audrito, Giorgio, Damiani, Ferruccio, Torta, Gianluca |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783031751066 |
| Informácie o vydavateľovi: | Springer Nature Switzerland, 2024. |
| Rok vydania: | 2024 |
| Predmety: | Aggregate Computing, Programming abstractions, Real-time guarantees, Self-organising systems |
| Popis: | Developing large-scale collective adaptive systems for safety-critical applications requires an extensive effort, involving the interplay of distributed programming techniques and mathematical proofs of real-time guarantees. This effort could be significantly reduced by allowing the system developer to rely on libraries of predefined algorithms. By exploiting such algorithms, distributed behaviour and (hard) real-time guarantees for the final application could be automatically inferred, effectively shifting the verification burden from the system designer to the algorithm developer. Following earlier work on real-time guarantees for aggregate computing algorithms, we argue that aggregate computing could provide a convenient framework towards this aim. As a first step, we give a detailed description of different kinds of models that abstract aggregate programs as mathematical functions. Then, building on such models, we start investigating the problem of how real-time behavior constraints could be specified in a compositional way. Finally, we conclude by singling out a number of potential building block library algorithms that could constitute such a real-time aggregate computing library, with the potential of providing a valuable asset for supporting the rigorous engineering of safety-critical large-scale collective adaptive systems. |
| Druh dokumentu: | Part of book or chapter of book Conference object |
| Popis súboru: | application/pdf |
| Jazyk: | English |
| DOI: | 10.1007/978-3-031-75107-3_4 |
| Prístupová URL adresa: | https://hdl.handle.net/2318/2037057 https://doi.org/10.1007/978-3-031-75107-3_4 |
| Rights: | Springer Nature TDM |
| Prístupové číslo: | edsair.doi.dedup.....abccc98ce9ef17a67e5ac6a8bed0b938 |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | Developing large-scale collective adaptive systems for safety-critical applications requires an extensive effort, involving the interplay of distributed programming techniques and mathematical proofs of real-time guarantees. This effort could be significantly reduced by allowing the system developer to rely on libraries of predefined algorithms. By exploiting such algorithms, distributed behaviour and (hard) real-time guarantees for the final application could be automatically inferred, effectively shifting the verification burden from the system designer to the algorithm developer. Following earlier work on real-time guarantees for aggregate computing algorithms, we argue that aggregate computing could provide a convenient framework towards this aim. As a first step, we give a detailed description of different kinds of models that abstract aggregate programs as mathematical functions. Then, building on such models, we start investigating the problem of how real-time behavior constraints could be specified in a compositional way. Finally, we conclude by singling out a number of potential building block library algorithms that could constitute such a real-time aggregate computing library, with the potential of providing a valuable asset for supporting the rigorous engineering of safety-critical large-scale collective adaptive systems. |
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| DOI: | 10.1007/978-3-031-75107-3_4 |