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41
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 67 (5 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 52 (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.
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 40 (3 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.
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 32 (12 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
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 27 (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...
Establishing Qualitative Properties for Probabilistic Lossy Channel Systems: an Algorithmic Approach
 In Proceedings of 5th International AMAST Workshop on RealTime and Probabilistic Systems (ARTSâ€™99
, 1999
"... . Lossy channel systems (LCSs) are models for communicating systems where the subprocesses are linked via unbounded FIFO channels which might lose messages. Link protocols, such as the Alternating Bit Protocol and HDLC can be modelled with these systems. The decidability of several verification ..."
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Cited by 23 (5 self)
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. Lossy channel systems (LCSs) are models for communicating systems where the subprocesses are linked via unbounded FIFO channels which might lose messages. Link protocols, such as the Alternating Bit Protocol and HDLC can be modelled with these systems. The decidability of several verification problems of LCSs has been investigated by Abdulla & Jonsson [AJ93,AJ94], e.g. they have shown that the reachability problem for LCSs is decidable while LTL model checking is not. In this paper, we consider probabilistic LCSs (which are LCSs where the transitions are augmented with appropriate probabilities) as introduced by [IN97] and show that the question of whether or not a linear time property holds with probability 1 is decidable. More precisely, we show how LTL nX model checking for (certain types of) probabilistic LCSs can be reduced to a reachability problem in a (nonprobabilistic) LCS where the latter can be solved with the methods of [AJ93]. 1 1 Introduction Traditiona...
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 22 (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 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 19 (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
Metrics for Actionlabelled Quantitative Transition Systems
, 2005
"... This paper defines actionlabelled quantitative transition systems as a general framework for combining qualitative and quantitative analysis. We define statemetrics as a natural extension of bisimulation from nonquantitative systems to quantitative ones. We then prove that any single statemetric ..."
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Cited by 18 (5 self)
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This paper defines actionlabelled quantitative transition systems as a general framework for combining qualitative and quantitative analysis. We define statemetrics as a natural extension of bisimulation from nonquantitative systems to quantitative ones. We then prove that any single statemetric corresponds to a bisimulation and that the greatest statemetric corresponds to bisimilarity. Furthermore, we provide two extended examples which show that our results apply to both probabilistic and weighted automata as special cases of actionlabelled quantitative transition systems.