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Probabilistic Extensions of Process Algebras
 Handbook of Process Algebra
, 2001
"... INTRODUCTION Classic process, algebras such as CCS, CSP and ACP, are wellestablished techniques for modelling and reasoning about functional aspects of concurrent processes. The motivation for studying probabilistic extensions of process algebras is to develop techniques dealing with nonfunctiona ..."
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Cited by 80 (7 self)
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INTRODUCTION Classic process, algebras such as CCS, CSP and ACP, are wellestablished techniques for modelling and reasoning about functional aspects of concurrent processes. The motivation for studying probabilistic extensions of process algebras is to develop techniques dealing with nonfunctional aspects of process behavior, such as performance and reliability. We may want to investigate, e.g., the average response time of a system, or the ? This chapter is dedicated to the fond memory of Linda Christoff. probability that a certain failure occurs. An analysis of these and similar properties requires that some form of information about the stochastic distribution over the occurrence of relevant events is put into the model. For instance, performance evaluation is often based on modeling a system as a continuoustime Markov process, in which distributions over delays between actions and over the choice between different actions are specified. Similar
Process Algebra for Performance Evaluation
, 2000
"... This paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. A huge class of resourcesharing systems  like largescale computers, clientserver architectur ..."
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Cited by 71 (13 self)
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This paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. A huge class of resourcesharing systems  like largescale computers, clientserver architectures, networks  can accurately be described using such stochastic specification formalisms.
Comparative branchingtime semantics for Markov chains
 Information and Computation
, 2003
"... This paper presents various semantics in the branchingtime spectrum of discretetime and continuoustime Markov chains (DTMCs and CTMCs). Strong and weak bisimulation equivalence and simulation preorders are covered and are logically characterised in terms of the temporal logics PCTL (Probabilisti ..."
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Cited by 64 (17 self)
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This paper presents various semantics in the branchingtime spectrum of discretetime and continuoustime Markov chains (DTMCs and CTMCs). Strong and weak bisimulation equivalence and simulation preorders are covered and are logically characterised in terms of the temporal logics PCTL (Probabilistic Computation Tree Logic) and CSL (Continuous Stochastic Logic). Apart from presenting various existing branchingtime relations in a uniform manner, this paper presents the following new results: (i) strong simulation for CTMCs, (ii) weak simulation for CTMCs and DTMCs, (iii) logical characterizations thereof (including weak bisimulation for DTMCs), (iv) a relation between weak bisimulation and weak simulation equivalence, and (v) various connections between equivalences and preorders in the continuous and discretetime setting. The results are summarized in a branchingtime spectrum for DTMCs and CTMCs elucidating their semantics as well as their relationship. Key Words: comparative semantics, Markov chain, (weak) simulation, (weak) bisimulation, temporal logic
Weak bisimulation for probabilistic systems
 CONCURRENCY THEORY, LNCS
, 2000
"... In this paper, we introduce weak bisimulation in the framework of Labeled Concurrent Markov Chains, that is, probabilistic transition systems which exhibit both probabilistic and nondeterministic behavior. By resolving the nondeterminism present, these models can be decomposed into a possibly infini ..."
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Cited by 59 (8 self)
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In this paper, we introduce weak bisimulation in the framework of Labeled Concurrent Markov Chains, that is, probabilistic transition systems which exhibit both probabilistic and nondeterministic behavior. By resolving the nondeterminism present, these models can be decomposed into a possibly infinite number of computation trees. We show that in order to compute weak bisimulation it is sufficient to restrict attention to only a finite number of these computations. Finally, we present an algorithm for deciding weak bisimulation which has polynomialtime complexity in the number of states of the transition system.
Bisimulation Algorithms for Stochastic Process Algebras and their BDDbased Implementation
 In ARTS, LNCS 1601
, 1999
"... . Stochastic process algebras have been introduced in order to enable compositional performance analysis. The size of the state space is a limiting factor, especially if the system consists of many cooperating components. To fight state space explosion, various proposals for compositional aggregatio ..."
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Cited by 36 (13 self)
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. Stochastic process algebras have been introduced in order to enable compositional performance analysis. The size of the state space is a limiting factor, especially if the system consists of many cooperating components. To fight state space explosion, various proposals for compositional aggregation have been made. They rely on minimisation with respect to a congruence relation. This paper addresses the computational complexity of minimisation algorithms and explains how efficient, BDDbased data structures can be employed for this purpose. 1 Introduction Compositional application of stochastic process algebras (SPA) is particularly successful if the system structure can be exploited during Markov chain generation. For this purpose, congruence relations have been developed which justify minimisation of components without touching behavioural properties. Examples of such relations are strong equivalence [22], (strong and weak) Markovian bisimilarity [16] and extended Markovian bisimi...
Probabilistic Noninterference through Weak Probabilistic Bisimulation
, 2003
"... To be practical, systems for ensuring secure information flow must be as permissive as possible. To this end, the author recently proposed a type system for multithreaded programs running under a uniform probabilistic scheduler; it allows the running times of threads to depend on the values of var ..."
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Cited by 33 (3 self)
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To be practical, systems for ensuring secure information flow must be as permissive as possible. To this end, the author recently proposed a type system for multithreaded programs running under a uniform probabilistic scheduler; it allows the running times of threads to depend on the values of variables, provided that these timing variations cannot affect the values of variables. But these timing variations preclude a proof of the soundness of the type system using the framework of probabilistic bisimulation, because probabilistic bisimulation is too strict regarding time. To address this difficulty, this paper proposes a notion of weak probabilistic bisimulation for Markov chains, allowing two Markov chains to be regarded as equivalent even when one "runs" more slowly than the other. The paper applies weak probabilistic bisimulation to prove that the type system guarantees the probabilistic noninterference property. Finally, the paper shows that the language can safely be extended with a fork command that allows new threads to be spawned. 1
Decision Algorithms for Probabilistic Bisimulation
, 2002
"... We propose decision algorithms for bisimulation relations de ned on probabilistic automata, a model for concurrent nondeterministic systems with randomization. The algorithms decide both strong and weak bisimulation relations based on deterministic as well as randomized schedulers. These algori ..."
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Cited by 32 (3 self)
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We propose decision algorithms for bisimulation relations de ned on probabilistic automata, a model for concurrent nondeterministic systems with randomization. The algorithms decide both strong and weak bisimulation relations based on deterministic as well as randomized schedulers. These algorithms extend and complete other known algorithms for simpler relations and models. The algorithm we present for strong probabilistic bisimulation has polynomial time complexity, while the algorithm for weak probabilistic bisimulation is exponential; however we argue that the latter is feasible in practice.
Probabilistic Reachability for Parametric Markov Models
"... Given a parametric Markov model, we consider the problem of computing the formula expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression is compute ..."
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Cited by 29 (4 self)
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Given a parametric Markov model, we consider the problem of computing the formula expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression is computed. Afterwards, this expression is evaluated to a closed form expression representing the reachability probability. This paper investigates how this idea can be turned into an effective procedure. It turns out that the bottleneck lies in an exponential growth of the regular expression relative to the number of states. We therefore proceed differently, by tightly intertwining the regular expression computation with its evaluation. This allows us to arrive at an effective method that avoids the exponential blow up in most practical cases. We give a detailed account of the approach, also extending to parametric models with rewards and with nondeterminism. Experimental evidence is provided, illustrating that our implementation provides meaningful insights on nontrivial models.
Weak Bisimulation is Sound and Complete for PCTL
, 2002
"... We investigate weak bisimulation of probabilistic systems in the presence of nondeterminism, i.e. labelled concurrent Markov chains (LCMC) with silent transitions. We build on the work of Philippou, Lee and Sokolsky [1] for finite state LCMCs. Their denition of weak bisimulation destroys the additiv ..."
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Cited by 26 (0 self)
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We investigate weak bisimulation of probabilistic systems in the presence of nondeterminism, i.e. labelled concurrent Markov chains (LCMC) with silent transitions. We build on the work of Philippou, Lee and Sokolsky [1] for finite state LCMCs. Their denition of weak bisimulation destroys the additivity property of the probability distributions, yielding instead capacities. The mathematics behind capacities naturally captures the intuition that when we deal with nondeterminism we must work with estimates on the possible probabilities. Our analysis leads to three...