Large Deviations For Performance Analysis: QUEUES, Communication and Computing (Stochastic Modeling Series)
| Author | : | |
| Rating | : | 4.32 (919 Votes) |
| Asin | : | 0412063115 |
| Format Type | : | paperback |
| Number of Pages | : | 560 Pages |
| Publish Date | : | 2018-02-05 |
| Language | : | English |
DESCRIPTION:
"This book is a successful attempt to apply a sophisticated new mathematic technique, the theory of large deviations, to a broad class of problems in performance analysis of large systems." --Zentralblatt
This book consists of two synergistic parts. Features: A transient analysis of the M/M/1 queue; a new analysis of an Aloha model using Markov modulated theory; new results for Erlang's model; new results for the AMS model; analysis of "serve the longer queue", "join the shorter queue" and other simple priority queues; and a simple analysis of the Flatto-Hahn-Wright model of processor-sharing.. The second half is a collection of applications developed at Bell Laboratories. The first half develops the theory of large deviations from the beginning (iid random variables) through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. Within its scope, the treatment is detailed, comprehensive and self-contained. Aspects of parallel computation are covered as well: basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The applications cover large areas of the theory of communication networks: circuit
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