@inproceedings{eprints3067, publisher = {IEEE}, month = {July}, author = {Danilo Pianini and Stefano Sebastio and Andrea Vandin}, pages = {416--423}, booktitle = {2014 International Conference on High Performance Computing \& Simulation (HPCS)}, title = {Distributed statistical analysis of complex systems modeled through a chemical metaphor}, year = {2014}, keywords = {Discrete event simulation; Distributed programming; Multiprocessing systems; Statistical analysis; Alchemist tool; MultiVeSta tool; Chemical metaphor; Chemical-inspired computational systems; Complex systems; Context-aware devices; Densely distributed devices}, url = {http://eprints.imtlucca.it/3067/}, 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.} }