A compositional approach to performance modelling
A compositional approach to performance modelling
An Efficient Kronecker Representation for PEPA Models
PAPM-PROBMIV '01 Proceedings of the Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Process Algebras for Quantitative Analysis
LICS '05 Proceedings of the 20th Annual IEEE Symposium on Logic in Computer Science
Tuning Systems: From Composition to Performance
The Computer Journal
Fluid Flow Approximation of PEPA models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
State-Aware Performance Analysis with eXtended Stochastic Probes
EPEW '08 Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering
Stochastic Simulation Methods Applied to a Secure Electronic Voting Model
Electronic Notes in Theoretical Computer Science (ENTCS)
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We report on our use of quantitative modelling in predicting the success of systems and services in achieving Service Level Agreements (SLAs). We construct models of the systems in the stochastic process algebra PEPA[1], and queries in the language of eXtended Stochastic Probes (XSP[2]). The query and model together are translated into an underlying continuous time Markov chain (CTMC) which is evaluated in order to assess the SLA. This most often requires a passage-time analysis where a passage (sequence of activity observations) is specified and the numerical analysis returns a function mapping the probability of completing the passage against time since the passage was initiated.