Encoding Timed Models as Uniform Labeled Transition Systems

Bernardo, Marco; Tesei, Luca

doi:10.1007/978-3-642-40725-3_9

Cited by 7 publications

(14 citation statements)

References 24 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We would like to continue the investigation started in [9] to compare in the uniform framework of ULTraS [7] the various deterministically timed and stochastically timed models and languages that have been proposed in the literature. This is not an easy task, as the differences between deterministic time and stochastic time are far more radical than those between integrated time and orthogonal time.…”

Section: Future Workmentioning

confidence: 99%

Timed process calculi with deterministic or stochastic delays: Commuting between durational and durationless actions

Bernardo

Corradini

Tesei

2016

Theoretical Computer Science

Self Cite

View full text Add to dashboard Cite

Several deterministically/stochastically timed process calculi have been proposed in the literature that, apart from their synchronization mechanism, mainly differ for the way in which actions and delays are represented. In particular, a distinction is made between integrated-time calculi, in which actions are durational, and orthogonal-time calculi, in which actions are instantaneous and delays are expressed separately. In a previous work on deterministic time, the two approaches have been shown to be reconcilable through an encoding from the integrated-time calculus CIPA to the orthogonal-time calculus TCCS, which preserves strong timed bisimilarity under certain conditions. In this paper, the picture is completed by first defining a reverse encoding from TCCS to CIPA, which requires slight modifications to both calculi and is shown to preserve only weak timed bisimilarity under conditions tighter than those for the direct encoding. Stochastic time is then addressed, by exhibiting an encoding from the integrated-time calculus MTIPP to the orthogonal-time calculus IML, together with a reverse encoding requiring slight modifications only to the former calculus, with both encodings being shown to preserve strong Markovian bisimilarity under suitable conditions. All the four encodings rely on the assumption that action execution is urgent. Variants are finally discussed in which action execution is delayable, in the sense that an enabled action can let time advance before starting its execution, or only the execution of internal actions is urgent, which is known as maximal progress

show abstract

Section: Future Workmentioning

confidence: 99%

Timed process calculi with deterministic or stochastic delays: Commuting between durational and durationless actions

Bernardo

Corradini

Tesei

2016

Theoretical Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…The formal definition of fluid trace equivalence resembles that of ordinary Markovian trace equivalence, proposed on transition-labeled CTMCs in [83], on sequential and concurrent Markovian process calculi SMPC and CMPC in [14,18,15,16,19] and on Uniform Labeled Transition Systems (ULTraS) in [21,22,17]. While defining fluid trace equivalence, we additionally have to take into account the fluid flow rates in the corresponding discrete markings of two compared LFSPNs.…”

Section: Fluid Trace Equivalencementioning

confidence: 99%

“…Therefore, our definition of the trace equivalence on the discrete markings of LFSPNs is similar to that of ordinary (that with the absolute time counter or with the countdown timer) Markovian trace equivalence [83] on transition-labeled CTMCs. Ordinary Markovian trace equivalence and its variants from [83] have been later investigated and enhanced on interactive Markov chains (IMCs) in [84], on sequential and concurrent Markovian process calculi SMPC and CMPC in [14,18,15,16,19], on Uniform Labeled Transition Systems (ULTraS) in [21,22,17], on continuous time Markov decision processes (CTMDPs) in [66] and on Markov automata (MAs) in [67]. As for the continuous markings of the two LFSPNs, we further select the paths with the same extracted action sequence and the same sequence of the extracted average sojourn times (exit rates) by counting the execution probabilities only of those paths additionally having the same sequence of extracted potential fluid flow rates of the respective continuous places (we assume that each compared LFSPN has only one continuous place) in the corresponding discrete markings.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, our definition of the bisimulation equivalence on the discrete markings of LFSPNs is similar to that of the performance bisimulation equivalences [28,29] on labeled CTSPNs and labeled generalized SPNs (GSPNs) [60,61,12,13], as well as the strong equivalence from [53] on stochastic process algebra PEPA. All these relations belong to the family of Markovian bisimulation equivalences, investigated on sequential and concurrent Markovian process calculi SMPC and CMPC in [14,18,15,16,19], as well as on Uniform Labeled Transition Systems (ULTraS) in [21,22,17]. As for the continuous markings, we require that, for every pair of the Markovian bisimilar discrete markings, the fluid flow rate of the continuous place in the first LFSPN should coincide with that of the continuous place in the second LFSPN (again, we compare only LFSPNs with a single continuous place each).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Logical characterization of fluid equivalences

Tarasyuk¹,

Buchholz²

2019

Sib. Elektron. Mat. Izv.

View full text Add to dashboard Cite

We investigate fluid equivalences that allow one to compare and reduce behaviour of labeled fluid stochastic Petri nets (LFSPNs) with a single continuous place while preserving their discrete and continuous properties. We propose a linear-time relation of fluid trace equivalence and its branching-time counterpart, fluid bisimulation equivalence. Both fluid relations take into account the essential features of the LFSPNs behaviour, such as functional activity, stochastic timing and fluid flow. We consider the LFSPNs whose continuous markings have no influence to the discrete ones, i.e. every discrete marking determines completely both the set of enabled transitions, their firing rates and the fluid flow rates of the incoming and outgoing arcs for each continuous place. Moreover, we require that the discrete part of the LFSPNs should be continuous time stochastic Petri nets. The underlying stochastic model for the discrete part of the LFSPNs is continuous time Markov chains (CTMCs). The performance analysis of the continuous part of LFSPNs is accomplished via the associated stochastic fluid models (SFMs). We characterize logically fluid trace and bisimulation equivalences with two novel fluid modal logics HM L f lt and HM L f lb , constructed on the basis of the well-known Hennessy-Milner Logic (HML). These characterizations guarantee that two LFSPNs are fluid (trace or bisimulation) equivalent iff they satisfy the same formulas of the respective logic, i.e. they are logically equivalent. The results imply operational characterizations of the logical equivalences.

show abstract

“…A state describes a static feature of the behavior of the system during its evolution, while a transition models how the system can evolve from one state to another. The basic formalism has been generalized in order to model timed [29] and hybrid systems [30]. In this paper, automata are equipped with topological information in order to model data-based complex systems.…”

Section: Persistent Entropy Automatonmentioning

confidence: 99%

Topological Characterization of Complex Systems: Using Persistent Entropy

Merelli

Rucco

Sloot

et al. 2015

Entropy

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a methodology for deriving a model of a complex system by exploiting the information extracted from topological data analysis. Central to our approach is the S[B] paradigm in which a complex system is represented by a two-level model. One level, the structural S one, is derived using the newly-introduced quantitative concept of persistent entropy, and it is described by a persistent entropy automaton. The other level, the behavioral B one, is characterized by a network of interacting computational agents. The presented methodology is applied to a real case study, the idiotypic network of the mammalian immune system.

show abstract

Encoding Timed Models as Uniform Labeled Transition Systems

Cited by 7 publications

References 24 publications

Timed process calculi with deterministic or stochastic delays: Commuting between durational and durationless actions

Timed process calculi with deterministic or stochastic delays: Commuting between durational and durationless actions

Logical characterization of fluid equivalences

Topological Characterization of Complex Systems: Using Persistent Entropy

Contact Info

Product

Resources

About