A5035860397- Formal Methods in Verification
- Gene Regulatory Network Analysis
- Petri Nets in System Modeling
- Advanced Software Engineering Methodologies
- Simulation Techniques and Applications
- Distributed systems and fault tolerance
- Business Process Modeling and Analysis
- Microbial Metabolic Engineering and Bioproduction
- Software System Performance and Reliability
- Software Reliability and Analysis Research
- Service-Oriented Architecture and Web Services
- Embedded Systems Design Techniques
- Bioinformatics and Genomic Networks
- Real-Time Systems Scheduling
- Mobile Agent-Based Network Management
- Distributed and Parallel Computing Systems
- Advanced Queuing Theory Analysis
- Evolution and Genetic Dynamics
- Parallel Computing and Optimization Techniques
- Model-Driven Software Engineering Techniques
- Bayesian Modeling and Causal Inference
- Receptor Mechanisms and Signaling
- Network Traffic and Congestion Control
- DNA and Biological Computing
- Advanced Database Systems and Queries
University of Edinburgh
2015-2024
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
2015-2018
University of Trieste
2015
Saarland University
2015
Universities UK
2002
In this paper we present a novel performance analysis technique for large scale systems modelled in the stochastic process algebra PEPA. contrast to well-known approach of analysing via continuous time Markov chains, our underlying mathematical representation is set coupled ordinary differential equations (ODEs). This supports all comhinators PEPA and well suited with numbers replicated components. The presents an elegant procedure generation ODEs compares results more conventional methods.
The exact performance analysis of large-scale software systems with discrete-state approaches is difficult because the well-known problem state-space explosion. This paper considers this regard to stochastic process algebra PEPA, presenting a deterministic approximation underlying Markov chain model based on ordinary differential equations. accuracy assessed by means substantial case study distributed multithreaded application.
In this work we introduce Bio-PEPA, a process algebra for the modelling and analysis of biochemical networks. It is modification PEPA to deal with some features biological models, such as stoichiometry use generic kinetic laws. Bio-PEPA may be seen an intermediate, formal, compositional representation systems, on which different kinds can carried out. Finally, show model, concerning simple genetic network, in new language.
In the 1980s process algebras became widely accepted formalisms for describing and analysing concurrency. Extensions of formalisms, incorporating some aspects systems which had previously been abstracted, were developed a number different purposes. area performance analysis models must quantify both timing probability. Addressing this domain led to formulation stochastic algebras. paper we give brief overview problems motivated them, before focussing on their relationship with underlying...
Performance Evaluation Process Algebra (PEPA) is a formal language for performance modeling based on process algebra. It has previously been shown that, by using the algebra apparatus, compact models can be derived which retain essential behavioral characteristics of modeled system. However, no efficient algorithm this derivation was given. We present an recognizes and takes advantage symmetries within model avoids unnecessary computation. The illustrated multiprocessor example.
Circadian clocks are gene regulatory networks whose role is to help the organisms cope with variations in environmental conditions such as day/night cycle. In this work, we explored effects of molecular noise single cells on behaviour circadian clock plant model species Arabidopsis thaliana . The computational modelling language Bio-PEPA enabled us give a stochastic interpretation an existing deterministic clock, and easily compare results obtained via simulation numerical solution model....