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EnglishThe chemical-inspired programming approach is an emerging paradigm for defining the behavior of densely distributed and context-aware devices (e.g., in ecosystems of displays tailored to crowd steering, or to obtain profile-based coordinated visualization). Typically, the evolution of such systems cannot be easily predicted, thus making of paramount importance the availability of techniques and tools supporting prior-to-deployment analysis. Exact analysis techniques do not scale well when the complexity of systems grows: as a consequence, approximated techniques based on simulation assumed a relevant role. This work presents a new simulation-based distributed analysis tool addressing the statistical analysis of such a kind of systems. The tool has been obtained by chaining two existing tools: MultiVeSta and Alchemist. The former is a recently proposed lightweight tool which allows to enrich existing discrete event simulators with automated and distributed statistical analysis capabilities, while the latter is an efficient simulator for chemical-inspired computational systems. The tool is validated against a crowd steering scenario, and insights on the performance are provided by discussing how the analysis tasks scale on a multi-core architecture.
| Titolo: | Distributed statistical analysis of complex systems modeled through a chemical metaphor |
| Autore/i: | PIANINI, DANILO; Stefano Sebastio; Andrea Vandin |
| Autore/i Unibo: | |
| Anno: | 2014 |
| Titolo del libro: | Proceedings of the 2014 International Conference on High Performance Computing and Simulation, HPCS 2014 |
| Pagina iniziale: | 416 |
| Pagina finale: | 423 |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/HPCSim.2014.6903715 |
| Abstract: | The chemical-inspired programming approach is an emerging paradigm for defining the behavior of densely distributed and context-aware devices (e.g., in ecosystems of displays tailored to crowd steering, or to obtain profile-based coordinated visualization). Typically, the evolution of such systems cannot be easily predicted, thus making of paramount importance the availability of techniques and tools supporting prior-to-deployment analysis. Exact analysis techniques do not scale well when the complexity of systems grows: as a consequence, approximated techniques based on simulation assumed a relevant role. This work presents a new simulation-based distributed analysis tool addressing the statistical analysis of such a kind of systems. The tool has been obtained by chaining two existing tools: MultiVeSta and Alchemist. The former is a recently proposed lightweight tool which allows to enrich existing discrete event simulators with automated and distributed statistical analysis capabilities, while the latter is an efficient simulator for chemical-inspired computational systems. The tool is validated against a crowd steering scenario, and insights on the performance are provided by discussing how the analysis tasks scale on a multi-core architecture. |
| Data prodotto definitivo in UGOV: | 12-gen-2015 |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11585/410572
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