Oxford logo
[Nor04] G. Norman. Analysing Randomized Distributed Algorithms. In C. Baier, B. Haverkort, H. Hermanns, J-P. Katoen, M. Siegle and F. Vaandrager (editors), Validation of Stochastic Systems: A Guide to Current Research, volume 2925 of Lecture Notes in Computer Science, pages 384--418, Springer. October 2004. [ps.gz] [pdf] [bib]
Downloads:  ps.gz ps.gz (133 KB)  pdf pdf (649 KB)  bib bib
Notes: The original publication is available at link.springer.com.
Front cover Abstract. Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.

QAV:

Home

People

Projects

Publications