Symbolically Quantifying Response Time in Stochastic Models using Moments and Semirings

Hugo Bazille (1) , Eric Fabre (1) , Blaise Genest (1)

1 SUMO - SUpervision of large MOdular and distributed systems

We study quantitative properties of the response time in stochastic models. For instance, we are interested in quantifying bounds such that a high percentage of the runs answers a query within these bounds. To study such problems, computing probabilities on a state-space blown-up by a factor depending on the bound could be used, but this solution is not satisfactory when the bound is large. In this paper, we propose a new symbolic method to quantify bounds on the response time, using the moments of the distribution of simple stochastic systems. We prove that the distribution (and hence the bounds) is uniquely defined given its moments. We provide optimal bounds for the response time over all distributions having a pair of these moments. We explain how to symbolically compute in polynomial time any moment of the distribution of response times using adequately-defined semirings. This allows us to compute optimal bounds in parametric models and to reduce complexity for computing optimal bounds in hierarchical models.

Domaines: Autre [cs.OH]

Hugo Bazille, Eric Fabre, Blaise Genest. Symbolically Quantifying Response Time in Stochastic Models using Moments and Semirings. FOSSACS 2018 - 21st International Conference on Foundations of Software Science and Computation Structures, Apr 2018, Thessaloniki, Greece. pp.403-419, ⟨10.1007/978-3-319-89366-2_22⟩. ⟨hal-01943440⟩