Performance analysis of stochastic process algebra models using stochastic simulation

J.T. Bradley; S.T. Gilmore; N. Thomas

doi:10.1109/IPDPS.2006.1639627

Performance analysis of stochastic process algebra models using stochastic simulation

J.T. Bradley, S.T. Gilmore, N. Thomas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process description, we can use tools developed for chemical and biochemical reaction analysis to provide time-series output for models with state spaces of O(10¹⁰⁰⁰⁰) and beyond. We apply these techniques to a significant case study: that of a secure electronic voting protocol.

Original language	English
Title of host publication	Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	10
ISBN (Print)	1-4244-0054-6
DOIs	https://doi.org/10.1109/IPDPS.2006.1639627
Publication status	Published - 1 Apr 2006

Keywords / Materials (for Non-textual outputs)

process algebra
simulation
state-space methods
stochastic processes
time series
biochemical reaction analysis
chemical reaction analysis
performance analysis
secure electronic voting protocol
stochastic process algebra model
stochastic simulation
Algebra
Analytical models
Biochemical analysis
Chemical analysis
Chemical processes
Equations
Performance analysis
State-space methods
Stochastic processes
Time series analysis

Access to Document

10.1109/IPDPS.2006.1639627

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1639627

Cite this

@inproceedings{b2dd02bcb58742b998673f4d4785c647,

title = "Performance analysis of stochastic process algebra models using stochastic simulation",

abstract = "We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process description, we can use tools developed for chemical and biochemical reaction analysis to provide time-series output for models with state spaces of O(1010000) and beyond. We apply these techniques to a significant case study: that of a secure electronic voting protocol.",

keywords = "process algebra, simulation, state-space methods, stochastic processes, time series, biochemical reaction analysis, chemical reaction analysis, performance analysis, secure electronic voting protocol, stochastic process algebra model, stochastic simulation, Algebra, Analytical models, Biochemical analysis, Chemical analysis, Chemical processes, Equations, Performance analysis, State-space methods, Stochastic processes, Time series analysis",

author = "J.T. Bradley and S.T. Gilmore and N. Thomas",

year = "2006",

month = apr,

day = "1",

doi = "10.1109/IPDPS.2006.1639627",

language = "English",

isbn = "1-4244-0054-6 ",

booktitle = "Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

}

TY - GEN

T1 - Performance analysis of stochastic process algebra models using stochastic simulation

AU - Bradley, J.T.

AU - Gilmore, S.T.

AU - Thomas, N.

PY - 2006/4/1

Y1 - 2006/4/1

N2 - We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process description, we can use tools developed for chemical and biochemical reaction analysis to provide time-series output for models with state spaces of O(1010000) and beyond. We apply these techniques to a significant case study: that of a secure electronic voting protocol.

AB - We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process description, we can use tools developed for chemical and biochemical reaction analysis to provide time-series output for models with state spaces of O(1010000) and beyond. We apply these techniques to a significant case study: that of a secure electronic voting protocol.

KW - process algebra

KW - simulation

KW - state-space methods

KW - stochastic processes

KW - time series

KW - biochemical reaction analysis

KW - chemical reaction analysis

KW - performance analysis

KW - secure electronic voting protocol

KW - stochastic process algebra model

KW - stochastic simulation

KW - Algebra

KW - Analytical models

KW - Biochemical analysis

KW - Chemical analysis

KW - Chemical processes

KW - Equations

KW - Performance analysis

KW - State-space methods

KW - Stochastic processes

KW - Time series analysis

U2 - 10.1109/IPDPS.2006.1639627

DO - 10.1109/IPDPS.2006.1639627

M3 - Conference contribution

SN - 1-4244-0054-6

BT - Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International

PB - Institute of Electrical and Electronics Engineers

ER -

Performance analysis of stochastic process algebra models using stochastic simulation

Abstract

Keywords / Materials (for Non-textual outputs)

Access to Document

Fingerprint

Cite this