J.-P. Katoen, E. Brinksma, D. Latella and R. Langerak. Stochastic simulation of event structures. In [89], pages 21--40.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....probability distribution. However, unlike EMPA the possibility of describing priorities is missing. Also, it is worth pointing out the lack of an integrated notion of action, viewed as being made out of a type and a duration, which could be more appealing from the modeling point of view. In [10] a stochastic process algebra is defined where each action is composed of a type and an arbitrarily distributed delay, and the semantics is defined in terms of stochastic bundle event structures instead of interleaving state transition graphs, thus resulting in a more elegant treatment of general ....

J.-P. Katoen, E. Brinksma, D. Latella, R. Langerak, "Stochastic Simulation of Event Structures", to appear in Proc. of the 4th Workshop on Process Algebras and Performance Modelling (PAPM '96), 1996

....are mainly followed: one is focussed on the purely # Supported by the NWO SION project 612 33 006. analytical study by restricting to the so called Markovian process algebras [14, 9, 2, the other addresses a more general case by accepting simulation as part of the analysis process [11, 16, 6, 7]. Recently, in [6] we introduced a simple extension of automata with stochastic information by borrowing ideas from timed automata [1] and generalised semiMarkov processes [8] In addition, we introduced a stochastic process algebra for discrete event simulation, named spades and denoted by . In ....

....algebras, basically CCS and its synchronous variant SCCS, to provide a denotational semantics of DEMOS. These works do not formalise the probabilistic information present in the original language and the role of process algebra with respect to simulation is di#erent from ours. Katoen et al. [16] used generalised semi Markov processes (GSMPs) indirectly as a semantic model: they map a non Markovian stochastic process algebra onto event structures, and obtain for a subclass of event structures (the so called stochastic deterministic ones) a GSMP. This translation induces a straightforward ....

[Article contains additional citation context not shown here]

J.-P. Katoen, E. Brinksma, D. Latella, and R. Langerak. Stochastic simulation of event structures. In M. Ribaudo, ed., Proc. of PAPM'96, Torino, Italy, pp. 21--40. Universita di Torino, 1996.

.... semantics has been defined in an operational way, thereby making it possible to build the state space on a by need basis (a routine for the simulative analysis of EMPA terms is going to be introduced in TwoTowers) Former algebraic approaches to discrete event simulation can be found in [HS95, KBLL96]. 8. How can the integrated approach of Fig. 1 be scaled to general distributions Although the combined use of exponentially timed and immediate actions allows us to model or approximate many frequently occurring distributions, from the modeling point of view it is advantageous to be able to ....

J.-P. Katoen, E. Brinksma, R. Langerak, D. Latella, "Stochastic Simulation of Event Structures", in [PAPM96], pp. 21-40

.... resulting in prioritized process algebras (see e.g. 4, 14, 13, 57, 17, 15] probabilistic process algebras (see e.g. 47, 30, 58, 37, 34, 5, 56] deterministically timed process algebras (see e.g. 52, 3, 41, 51, 39, 20, 60, 23, 36, 19] and stochastically timed process algebras (see e.g. [42, 24, 27, 12, 2, 21, 53, 26, 11, 45, 25, 31, 46]) The enhanced expressive power achieved by these classes of process algebras has allowed to model and analyze a greater number of characteristics with respect to classical process algebras such as interrupt mechanisms, resources where tasks having different priorities may arrive, loss ....

J.-P. Katoen, E. Brinksma, R. Langerak, D. Latella, "Stochastic Simulation of Event Structures", in [50], pp. 21-40

....et al. 18] proposed to use a non interleaving semantics (using event structures) to deal with more general distributions. The derivation of discrete event simulation models like GSMPs (Generalised Semi Markov Processes [95] from these extended event structures was presented in Katoen et al. [70]. Other non interleaving approaches are the variant of the stochastic # calculus of Priami [87] based on decorated transition systems, and the (informal) approach based on stochastic task graphs structures for which e#cient numerical and approximative analysis methods do exist by Herzog ....

J.-P. Katoen, E. Brinksma, D. Latella and R. Langerak. Stochastic simulation of event structures. In [89], pages 21--40.

.... made: a stochastic extension of event structures has been defined where the delay of actions is determined by continuous random variables (Brinksma et al. 10] and an algorithm has been developed for performing discrete event simulation of (a subclass of) such event structures (Katoen et al. [22]) 3.2 Adding time to event structures Time is added to event structures in the following way. To specify the relative delay between causally dependent events time is associated to bundles, and in order to facilitate the specification of timing constraints on events that have no bundle pointing ....

J-P. Katoen, D. Latella, R. Langerak and E. Brinksma. Stochastic simulation of event structures. In M. Ribaudo, editor, Proceedings 4th Int. Workshop on Process Algebra and Performance Modelling, pages 21--40. C.L.U.T. Press, 1996.

.... connection to performance analysis has been made: a stochastic extension of event structures has been defined where the delay of actions is determined by continuous random variables [9] and an algorithm has been developed for performing discrete event simulation of such event structures [19]. 4 Adding time to event structures Time is added to event structures in the following way. To specify the relative delay between causally dependent events time is associated to bundles, and in order to facilitate the specification of timing constraints on events that have no bundle pointing to ....

J-P. Katoen, D. Latella, R. Langerak and E. Brinksma. Stochastic simulation of event structures. In M. Ribaudo, ed, Proceedings 4th Int. Workshop on Process Algebra and Performance Modelling, pages 21--40. C.L.U.T. Press, 1996.

....and Markov chains have thus been established, e.g. between bisimulation and lumping [12] In fact, our presented approach can be considered as a generalisation of this line of research using GSMPs rather than Markov chains. To our knowledge the use of a process algebra to specify GSMPs is novel. [14] used GSMPs indirectly: they map an extended process algebra onto event structures, and obtain for a subclass of event structures a GSMP. For recursive processes infinite event structures are obtained which makes this approach less suited for the use of efficient regenerative simulation ....

J.-P. Katoen, E. Brinksma, D. Latella, and R. Langerak. Stochastic simulation of event structures. In Proceedings PAPM'96, pp 21--40. CLUT Press, 1996.

....event simulation. In this paper we established a link between stochastic process algebras and discrete event simulation, in particular the more formal model of GSMPs. To our knowledge the use of (a variation of) GSMPs as a semantic model for stochastic process algebras is novel. Katoen et al. [17] indirectly used GSMPs as a semantic model: they map a non Markovian stochastic process algebra onto event structures, and obtain for a subclass of event structures (the so called stochastic deterministic ones) a GSMP. The intermediate model, event structures, has become obsolete in our approach. ....

....structures, and obtain for a subclass of event structures (the so called stochastic deterministic ones) a GSMP. The intermediate model, event structures, has become obsolete in our approach. In addition, for recursive processes infinite event structures are obtained which makes the approach of [17] less suited for the use of efficient regenerative simulation techniques. The finite representations we obtain do not suffer from this problem. The relation between process algebras and discrete event simulation models has been studied from several perspectives. Harrison Strulo [11] developed a ....

[Article contains additional citation context not shown here]

J.-P. Katoen, E. Brinksma, D. Latella, and R. Langerak. Stochastic simulation of event structures. In Ribaudo [23], pages 21--40.

....event simulation. In this paper we established a link between stochastic process algebras and discrete event simulation, in particular the more formal model of GSMPs. To our knowledge the use of (a variation of) GSMPs as a semantic model for stochastic process algebras is novel. Katoen et al. [17] indirectly used GSMPs as a semantic model: they map a non Markovian stochastic process algebra onto event structures, and obtain for a subclass of event structures (the so called stochastic deterministic ones) a GSMP. The intermediate model, event structures, has become obsolete in our approach. ....

....structures, and obtain for a subclass of event structures (the so called stochastic deterministic ones) a GSMP. The intermediate model, event structures, has become obsolete in our approach. In addition, for recursive processes infinite event structures are obtained which makes the approach of [17] less suited for the use of efficient regenerative simulation techniques. The finite representations we obtain do not suffer from this problem. The relation between process algebras and discrete event simulation models has been studied from several perspectives. Harrison Strulo [11] developed a ....

[Article contains additional citation context not shown here]

J.-P. Katoen, E. Brinksma, D. Latella, and R. Langerak. Stochastic simulation of event structures. In Ribaudo [23], pages 21--40.

....is that they closely resemble continuous time Markov chains, see [40] Unfortunately, when a non interleaving semantics is adopted the convenient direct relationship between the semantics of stochastic process algebras and Markov like models is lost. However, the authors have shown in [47] that it is possible to generate so called (time homogeneous) generalised semiMarkov processes starting from (a class of) stochastic event structures. GSMPs [77] are a generic model for the study of stochastic discrete event systems. For such models it is possible to generate simulation runs from ....

....performance analysis of formal models in a systematic and (semi )automated way. In this paper we have presented several quantitative extensions of the formal description technique LOTOS in a non interleaving setting. Performance analysis is not explicitly treated here and can be found elsewhere [47]. We argued that quantitative extensions are of particular use in a partial order setting since notions like time, probability and distributions are important at the lower levels of abstraction, where the internal structure of systems is relevant for correct design. Because quantitative ....

[Article contains additional citation context not shown here]

J-P. Katoen, E. Brinksma, D. Latella and R. Langerak. Stochastic simulation of event structures. In M. Ribaudo, ed, Proc. 4th Int. Workshop on Process Algebra and Performance Modelling, pages 21--40. C.L.U.T. Press, 1996.

No context found.

H. Brinksma, J.-P. Katoen, R. Langerak, and D. Latella. Stochastic simulation of event structures. In Ribaudo [63]. To appear.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC