- Abstract:
-
We present a technique for defining and extracting passage-time densities from high-level stochastic process algebra models. Our high-level formalism is PEPA, a popular Markovian process algebra for expressing compositional performance models. We introduce ipc, a tool which can process PEPA-specified passage-time densities and models by compiling the PEPA model and passage specification into the DNAmaca formalism. DNAmaca is an established modelling language for the low-level specification of very large Markov and semi-Markov chains. We provide performance results for ipc/DNAmaca and comparisons with another tool which supports PEPA, PRISM. Finally, we generate passage-time densities and quantiles for a case study of a high-availability web server.
- Copyright:
- 2006 by The University of Edinburgh. All Rights Reserved
- Links To Paper
- IEEE Explore page
- Copy on my home page
- Bibtex format
- @InProceedings{EDI-INF-RR-0771,
- author = {
Jeremy Bradley
and Nick Dingle
and Stephen Gilmore
and Will Knottenbelt
},
- title = {Derivation of passage-time densities in PEPA models using IPC: The Imperial PEPA Compiler},
- book title = {Proceedings of MASCOTS 2003 (Modeling, Analysis, and Simulation On Computer and Telecommunication Systems)},
- publisher = {IEEE Computer Society},
- year = 2003,
- month = {Oct},
- pages = {344-351},
- url = {http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=1240679},
- }
|
