A Stochastic Broadcast Pi-Calculus

In this paper we propose a stochastic broadcast PI-calculus which can be used to model server-client based systems where synchronization is always governed by only one participant. Therefore, there is no need to determine the joint synchronization rates. We also take immediate transitions into account which is useful to model behaviors with no impact on the temporal properties of a system. Since immediate transitions may introduce non-determinism, we will show how these non-determinism can be resolved, and as result a valid CTMC will be obtained finally. Also some practical examples are given to show the application of this calculus.Comment: In Proceedings QAPL 2011, arXiv:1107.074

A criterion for separating process calculi

We introduce a new criterion, replacement freeness, to discern the relative expressiveness of process calculi. Intuitively, a calculus is strongly replacement free if replacing, within an enclosing context, a process that cannot perform any visible action by an arbitrary process never inhibits the capability of the resulting process to perform a visible action. We prove that there exists no compositional and interaction sensitive encoding of a not strongly replacement free calculus into any strongly replacement free one. We then define a weaker version of replacement freeness, by only considering replacement of closed processes, and prove that, if we additionally require the encoding to preserve name independence, it is not even possible to encode a non replacement free calculus into a weakly replacement free one. As a consequence of our encodability results, we get that many calculi equipped with priority are not replacement free and hence are not encodable into mainstream calculi like CCS and pi-calculus, that instead are strongly replacement free. We also prove that variants of pi-calculus with match among names, pattern matching or polyadic synchronization are only weakly replacement free, hence they are separated both from process calculi with priority and from mainstream calculi.Comment: In Proceedings EXPRESS'10, arXiv:1011.601

Algorithmic product-form approximations of interacting stochastic models

A large variety of product-form solutions for continuous-time Markovian models can be derived by checking a set of structural properties of the underlying stochastic processes and a condition on their reversed rates. In previous work (Marin and Vigliotti (2010)) we have shown how to derive a large class of product-form solutions using a different formulation of the Reversed Compound Agent Theorem (GRCAT). We continue this line of work by showing that it is possible to exploit this result to approximate the steady-state distribution of non-product-form model interactions by means of product-form ones

CoBiC: Context-dependent BioambientCalculus.

In biological phenomena like osmosis, the rate of flow of water molecules in or out of biological compartments depends on the solute concentration and on other forces, like hydrostatic pressure. A similar example is the passive transport of ions in and out the cell membrane. In this paper, we address the problem of faithfully modelling these kind of phenomena with an adequate process calculus. We enhance the ambient calculus stochastic semantics with functional rates, which are calculated by taking into account the volume of ambients and the surrounding environment. A model of osmosis in plant cells will be used as an example to show the new features of our calculus