A survey of the PEPA tools

This paper surveys the history and the current state of tool support for modelling with the PEPA stochastic process algebra and the PEPA nets modelling language. We discuss future directions for tool support for the PEPA family of languages.

Fluid passage-time calculation in large Markov models

Recent developments in the analysis of large Markov models facilitate the fast approximation of transient characteristics of the underlying stochastic process. So-called fluid analysis makes it possible to consider previously intractable models whose underlying discrete state space grows exponentially as model components are added. In this work, we show how fluid approximation techniques may be used to extract passage-time measures from performance models. We focus on two types of passage measure: passage-times involving individual components; as well as passage-times which capture the time taken for a population of components to evolve. Specifically, we show that for models of sufficient scale, passage-time distributions can be well approximated by a deterministic fluid-derived passage-time measure. Where models are not of sufficient scale, we are able to generate approximate bounds for the entire cumulative distribution function of these passage-time random variables, using moment-based techniques. Finally, we show that for some passage-time measures involving individual components the cumulative distribution function can be directly approximated by fluid techniques

Nitrification Investigation And Modeling In The Chloraminated Drinking Water Distribution System

This dissertation consists of five papers concerning nitrification in chloraminated drinking water distribution systems in a one and a half year field study. Seven finished waters were produced from different treatment processes and distributed to eighteen pilot distribution systems (PDSs) that were made pipes taken from actual distribution systems. Unlined cast iron (UCI), galvanized steel (G), lined cast iron (LCI), and PVC pipes were used to build the PDSs. All finished waters were stabilized and chloraminated before entering the PDSs. This dissertation consists of five major parts. (1) System variations of nitrates, nitrites, DO, pH, alkalinity, temperature, chloramine residuals and hydraulic residence times (HRT) during biological nitrification are interrelated and discussed relative to nitrification, which demonstrated Stoichiometric relationships associated with conventional biochemical nitrification reactions. Ammonia is always released when chloramines are used for residual maintenance in drinking water distribution systems, which practically insures the occurrence of biological nitrification to some degree. Biological nitrification was initiated by a loss of chloramine residual brought about by increasing temperatures at a five day HRT, which was accompanied by DO loss and slightly decreased pH. Ammonia increased due to chloramine decomposition and then decreased as nitrification began. Nitrites and nitrates increased initially with time after the chloramine residual was lost but decreased if denitrification began. Dissolved oxygen limited nitrifier growth and nitrification. No significant alkalinity variation was observed during nitrification. Residual and nitrites are key parameters for monitoring nitrification in drinking water distribution systems. (2) Using Monod kinetics, a steady state plug-flow kinetics model was developed to describe the variations of ammonia, nitrite and nitrate-N concentrations in a chloraminated distribution system. Active AOB and NOB biomass in the distribution system was determined using predictive equations within the model. The kinetic model used numerical analysis and was solved by C language to predict ammonia, nitrite, nitrate variation. (3) Nitrification control strategies were investigated during an unexpected episode and controlled study in a field study. Once nitrification began, increasing chloramine dose from 4.0 to 4.5 mg/L as Cl2 and Cl2:N ratio from 4/1 to 5/1 did not stop nitrification. Nitrification was significantly reduced but not stopped, when the distribution system hydraulic retention time was decreased from 5 to 2 days. A free chlorine burn for one week at 5 mg/L Cl2 stopped nitrification. In a controlled nitrification study, nitrification increased with increasing free ammonia and Cl2:N ratios less than 5. Flushing with increased chloramine concentration reduced nitrification, but varying flush frequency from 1 to 2 weeks had no effect on nitrification. (4) HPC variations in a chloraminated drinking water distribution system were investigated. Results showed average residual and temperature were the only water quality variables shown to affect HPC change at a five day distribution system hydraulic residence time was five days. Once nitrification began, HPC change was correlated to HRT, average residual and generated nitrite-N in the distribution system. (5) Biostability was assessed for water treatment processes and distribution system pipe by AOCs, BDOCs, and HPCs of the bulk water, and by PEPAs of the attached biofilms. All membrane finished waters were more likely to be biologically stable as indicated by lower AOCs. RO produced the lowest AOC. The order of biofilm growth by pipe material was UCI \u3e G \u3e LCI \u3e PVC. Biostability decreased as temperature increased

ODE-based general moment approximations for PEPA

In this paper we show how the powerful ODE-based fluid-analysis technique for the stochastic process algebra PEPA is an approximation to the first moments of the counting processes in question. For a large class of models this approximation has a particularly simple form and it is possible to make qualitative statements regarding how the quality of the approximation varies for different parameters. Furthermore, this particular point of view facilitates a natural generalisation to higher order moments. This allows modellers to approximate, for instance, the variance of the component counts. In particular, we show how systems of ODEs facilitating the approximation of arbitrary moments of the component counting processes can be naturally defined. The effectiveness of this generalisation is illustrated by comparing the results with those obtained through stochastic simulation for a particular case study

Fluid semantics for passive stochastic process algebra cooperation

Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engineers. Therefore having an accurate translation of passive cooperation into a fluid model is of direct practical application. We compare different existing styles of fluid model translation of passive cooperation in a stochastic process algebra. We explain why the development of a fluid semantics for passive cooperation is not straightforward and we present an alternative definition which more closely matches the underlying discrete model. Finally, we present quantitative comparisons with a previous version of the fluid semantics in which numerical discrepancies can be observed. © 2008 ICST ISBN

Process algebra approach to parallel DBMS performance modelling

Abstract unavailable please refer to PD

Evaluating fluid semantics for passive stochastic process algebra cooperation

Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engineers. Therefore having an accurate translation of passive cooperation into a fluid model is of direct practical application. We compare different existing styles of fluid model translation of passive cooperation in a stochastic process algebra and show how the previous model can be improved upon significantly. We evaluate the new passive cooperation fluid semantics and show that the first-order fluid model is a good approximation to the dynamics of the underlying continuous-time Markov chain. We show that in a family of possible translations to the fluid model, there is an optimal translation which can be expected to introduce least error. Finally, we use these new techniques to show how the scalability of a passively-cooperating distributed software architecture could be assessed

Modeling formalisms in systems biology

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.Research supported by grants SFRH/BD/35215/2007 and SFRH/BD/25506/2005 from the Fundacao para a Ciencia e a Tecnologia (FCT) and the MIT-Portugal Program through the project "Bridging Systems and Synthetic Biology for the development of improved microbial cell factories" (MIT-Pt/BS-BB/0082/2008)

Proceedings of the Fifth Mediterranean Conference on Information Systems: Professional Development Consortium

Collection of position statements of doctoral students and junior faculty in the Professional Development Consortium at the the Fifth Mediterranean Conference on Information Systems, Tel Aviv - Yafo