Mobile Ambients (MA) have acquired a fundamental role in modelling mobility in systems with mobile code and mobile devices, and in computation over administrative domains. We present the stochastic version of Mobile Ambients, called Stochastic Mobile Ambients (SMA), where we extend MA with time and probabilities. Inspired by previous models, PEPA and S, we enhance the prefix of the capabilities with a rate and the ambient with a linear function that operates on the rates of processes executing inside it. The linear functions associated with ambients represent the delays that govern particular administrative domains. We derive performance measures from the labelled transition semantics as in standard models. We also define a strong Markov bisimulation in the style of reduction semantics known as barbed bisimulation. We argue that performance measures are of vital importance in designing any kind of distributed system, and that SMA can be useful in the design of the complicated mobile s...
Maria Grazia Vigliotti, Peter G. Harrison