Fluid Flow Approximation of PEPA models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
IEEE Transactions on Parallel and Distributed Systems
A fluid analysis framework for a Markovian process algebra
Theoretical Computer Science
A mean field model of work stealing in large-scale systems
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Mean field limit of non-smooth systems and differential inclusions
ACM SIGMETRICS Performance Evaluation Review
Fluid analysis of energy consumption using rewards in massively parallel markov models
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
On fluidization of discrete event models: observation and control of continuous Petri nets
Discrete Event Dynamic Systems
Hybrid Limits of Continuous Time Markov Chains
QEST '11 Proceedings of the 2011 Eighth International Conference on Quantitative Evaluation of SysTems
GPA - A Tool for Fluid Scalability Analysis of Massively Parallel Systems
QEST '11 Proceedings of the 2011 Eighth International Conference on Quantitative Evaluation of SysTems
Fluid computation of passage-time distributions in large Markov models
Theoretical Computer Science
Scalable Differential Analysis of Process Algebra Models
IEEE Transactions on Software Engineering
Moment closures for performance models with highly non-linear rates
EPEW'12 Proceedings of the 9th European conference on Computer Performance Engineering
Moment closures for performance models with highly non-linear rates
EPEW'12 Proceedings of the 9th European conference on Computer Performance Engineering
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We extend the population continuous time Markov chain formalism so that the state space is augmented with continuous variables accumulated over time as functions of component populations. System feedback can be expressed using accumulations that in turn can influence the Markov chain behaviour via functional transition rates. We show how to obtain mean-field differential equations capturing means and higher-order moments of the discrete populations and continuous accumulation variables. We also provide first- and second-order convergence results and suggest a novel normal moment closure that can greatly improve the accuracy of means and higher moments. We demonstrate how such a framework is suitable for modelling feedback from globally-accumulated quantities such as energy consumption, cost or temperature. Finally, we present a worked example modelling a hypothetical heterogeneous computing cluster and its interaction with air conditioning units.