AESOP home

Publications

Scalable Stochastic Modelling for Resilience

Jeremy T. Bradley, Lucia Cloth, Richard Hayden, Kloul, Philipp Reinecke, Markus Siegle, Nigel Thomas, Katinka Wolter

Book Chapter
Resilience Assessment and Evaluation of Computing Systems
November, 2012
pp.115–149
Springer
ISBN 978-3-642-29031-2
DOI 10.1007/978-3-642-29032-9_6
Abstract

This chapter summarises techniques that are suitable for performance and resilience modelling and analysis of massive stochastic systems. We will introduce scalable techniques that can be applied to models constructed using DTMCs and CTMCs as well as compositional formalisms such as stochastic automata networks, stochastic process algebras and queueing networks. We will briefly show how techniques such as mean value analysis, mean-field analysis, symbolic data structures and fluid analysis can be used to analyse massive models specifically for resilience in networks, communication and computer architectures.

PDF of full publication (723.4 kilobytes)
(need help viewing PDF files?)

Information from pubs.doc.ic.ac.uk/scalable-stochastic-modelling.