Abstract
We present a Model-Driven Engineering (MDE) approach to quantitative evaluation of stochastic models through the ORIS tool and the SIRIO library. As an example, the approach is applied to the case of a tramway line with reduced number of passengers to contain the spread of infection during a pandemic. Specifically, we provide a meta-model for this scenario, where, at each stop, only a certain number of people can ride the tram depending on the current tram capacity, the length of the queue of people waiting at the stop, and the number of passengers on the tram. Then, the ORIS tool and the SIRIO library are used as a software platform to derive a Stochastic Time Petri Net (STPN) representation for each tramway stop and to perform its regenerative transient analysis to obtain quantitative measures of interest, such as the expected number of people waiting at each stop and the expected number of tram passengers over time. Experimental results show that the approach facilitates exploration of the space of design choices, providing insight about the effects of parameter changes on quantitative measures of interest and allowing balanced queue sizes at different stops.
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Carnevali, L., Paolieri, M., Reali, R., Scommegna, L., Tammaro, F., Vicario, E. (2023). Using the ORIS Tool and the SIRIO Library for Model-Driven Engineering of Quantitative Analytics. In: Gilly, K., Thomas, N. (eds) Computer Performance Engineering. EPEW 2022. Lecture Notes in Computer Science, vol 13659. Springer, Cham. https://doi.org/10.1007/978-3-031-25049-1_13
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