Scalable Stochastic Modelling for Resilience
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.
KeywordsLabel Transition System Tensor Representation Binary Decision Diagram Negative Customer State Space Explosion Problem
Jeremy Bradley, Richard Hayden and Nigel Thomas are supported by the UK Engineering and Physical Sciences Research Council on the AMPS project (reference EP/G011737/1). Leïla Kloul is supported by the European Celtic project HOMESNET , Philipp Reinecke and Katinka Wolter are supported by the German Research Council under grant Wo 898/3-1.