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Verification of probabilistic systems with faulty communication
 IN PROCEEDINGS OF FOSSACS 2003
, 2003
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The verification of probabilistic lossy channel systems
 In Validation of Stochastic Systems – A Guide to Current Research, LNCS 2925
, 2004
"... Abstract. Lossy channel systems (LCS’s) are systems of finite state automata that communicate via unreliable unbounded fifo channels. Several probabilistic versions of these systems have been proposed in recent years, with the two aims of modeling more faithfully the losses of messages, and circumve ..."
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Cited by 16 (0 self)
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Abstract. Lossy channel systems (LCS’s) are systems of finite state automata that communicate via unreliable unbounded fifo channels. Several probabilistic versions of these systems have been proposed in recent years, with the two aims of modeling more faithfully the losses of messages, and circumventing undecidabilities by some kind of randomization. We survey these proposals and the verification techniques they support. 1
Probability and Nondeterminism in Operational Models of Concurrency
 In Proc. CONCUR, LNCS
, 2006
"... Abstract. We give a brief overview of operational models for concurrent systems that exhibit probabilistic behavior, focussing on the interplay between probability and nondeterminism. Our survey is carried out from the perspective of probabilistic automata, a model originally developed for the analy ..."
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Cited by 13 (1 self)
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Abstract. We give a brief overview of operational models for concurrent systems that exhibit probabilistic behavior, focussing on the interplay between probability and nondeterminism. Our survey is carried out from the perspective of probabilistic automata, a model originally developed for the analysis of randomized distributed algorithms. 1
Stochastic transition systems for continuous state spaces and nondeterminism
 In FoSSaCS’05, LNCS 3441
, 2005
"... Abstract. We study the interaction between nondeterministic and probabilistic behaviour in systems with continuous state spaces, arbitrary probability distributions and uncountable branching. Models of such systems have been proposed previously. Here, we introduce a model that extends probabilistic ..."
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Cited by 13 (4 self)
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Abstract. We study the interaction between nondeterministic and probabilistic behaviour in systems with continuous state spaces, arbitrary probability distributions and uncountable branching. Models of such systems have been proposed previously. Here, we introduce a model that extends probabilistic automata to the continuous setting. We identify the class of schedulers that ensures measurability properties on executions, and show that such measurability properties are preserved by parallel composition. Finally, we demonstrate how these results allow us to define an alternative notion of weak bisimulation in our model. 1
Probabilistic timed I/O automata with continuous state spaces. Preliminary version available at http://theory.lcs.mit.edu/˜mitras/research/ csptioa_preprint.pdf
, 2006
"... Abstract. We present Piecewise Deterministic Timed I/O Automata (PDTIOA): a new continuous state automaton model that allows both nondeterministic and probabilistic discrete transitions, along with continuous deterministic trajectories. We use a partition of actions, called tasks and a task schedule ..."
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Cited by 3 (3 self)
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Abstract. We present Piecewise Deterministic Timed I/O Automata (PDTIOA): a new continuous state automaton model that allows both nondeterministic and probabilistic discrete transitions, along with continuous deterministic trajectories. We use a partition of actions, called tasks and a task scheduler to resolve nondeterministic choice over actions. We define a topology on the set of trajectories and make a key continuity assumption about maximal length of trajectories. Together, these structures enable us to construct a natural probability measure over the space of executions and the space of traces. The resulting PDTIOA framework yields simple notions of external behavior and implementation, and has simple compositionality properties. By introducing local schedulers, we generalize PDTIOAs to allow nondeterministic trajectories and stopping times. 1
A Note on the AttractorProperty of InfiniteState Markov Chains
, 2005
"... In the past 5 years, a series of verification algorithms has been proposed for infinite Markov chains that have a finite attractor, i.e., a set that will be visited infinitely often almost surely starting from any state. In this paper, we establish a sufficient criterion for the existence of an attr ..."
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Cited by 3 (2 self)
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In the past 5 years, a series of verification algorithms has been proposed for infinite Markov chains that have a finite attractor, i.e., a set that will be visited infinitely often almost surely starting from any state. In this paper, we establish a sufficient criterion for the existence of an attractor. We show that if the states of a Markov chain can be given levels (positive integers) such that the expected next level for states at some level n > 0 if less than n for some positive D, then the states at level 0 constitute an attractor for the chain. As an application, we obtain a direct proof that some probabilistic channel systems combining message losses with duplication and insertion errors have a finite attractor.
Stochastic Reasoning About ChannelBased Component Connectors
"... Abstract. Constraint automata have been used as an operational model for component connectors that coordinate the cooperation and communication of the components by means of a network of channels. In this paper, we introduce a variant of constraint automata (called continuoustime constraint automat ..."
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Abstract. Constraint automata have been used as an operational model for component connectors that coordinate the cooperation and communication of the components by means of a network of channels. In this paper, we introduce a variant of constraint automata (called continuoustime constraint automata) that allows us to specify timedependent stochastic assumptions about the channel connections or the component interfaces, such as the arrival rates of communication requests, the average delay of enabled I/Ooperations at the channel ends or the stochastic duration of internal computations. This yields the basis for a performance analysis of channelbased coordination mechanisms. We focus on compositional reasoning and discuss several bisimulation relations on continuoustime constraint automata. For this, we adapt notions of strong and weak bisimulation that have been introduced for similar stochastic models and introduce a new notion of weak bisimulation which abstracts away from invisible nonstochastic computations as well as the internal stochastic evolution. 1
Verifying nondeterministic probabilistic channel systems against ωregular lineartime properties
, 2005
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Verifying Nondeterministic Channel Systems with Probabilistic Message Losses
, 2004
"... Lossy channel systems (LCS's) are systems of finite state automata that communicate via unreliable unbounded fifo channels. In order to circumvent the undecidability of model checking for nondeterministic LCS's, probabilistic models have been introduced, where it can be decided whether a l ..."
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Lossy channel systems (LCS's) are systems of finite state automata that communicate via unreliable unbounded fifo channels. In order to circumvent the undecidability of model checking for nondeterministic LCS's, probabilistic models have been introduced, where it can be decided whether a lineartime property holds almost surely. However, such fully probabilistic systems are not a faithful model of nondeterministic protocols.