Large Deviations for Gaussian Queues: Modelling Communication Networks ebook

by Michel Mandjes

In recent years the significance of Gaussian processes to communication networks has grown considerably.

In recent years the significance of Gaussian processes to communication networks has grown considerably. The inherent flexibility of the Gaussian traffic model enables the analysis, in a single mathematical framework, of systems with both long-range and short-range dependent input streams. Large Deviations for Gaussian Queues demonstrates how the Gaussian traffic model arises naturally, and how the analysis of the corresponding queuing model can be performed.

A large collection of instructive exercises and accompanying solutions. Michel Mandjes, Centre for Mathematics and Computer Science (CWI) Amsterdam, The Netherlands, and Professor, Faculty of Engineering, University of Twente

A large collection of instructive exercises and accompanying solutions. Large Deviations for Gaussian Queues assumes minimal prior knowledge. Michel Mandjes, Centre for Mathematics and Computer Science (CWI) Amsterdam, The Netherlands, and Professor, Faculty of Engineering, University of Twente. He has published for 60 papers on queuing theory, networks, scheduling, and pricing of networks.

Large deviations for Gaussian queues. Gaussian traffic everywhere? R Van De Meent, M Mandjes, A Pras. Marinucci, D. and Robinson, PM (1999). 2006 IEEE International Conference on Communications 2, 573-578, 2006. Large deviations for small buffers: an insensitivity result. M Mandjes, JH Kim. Queueing systems 37 (4), 349-362, 2001. M Mandjes, D Mitra, W Scheinhardt. Queueing Systems 44 (4), 365-398, 2003. Large deviations of sojourn times in processor sharing queues. Queueing Systems 52 (4), 237-250, 2006.

2 The Gaussian source model. Modeling network traffic. oceedings{Mandjes2007LargeDF, title {Large Deviations for Gaussian Queues: Modelling Communication Networks}, author {Michel Mandjes}, year {2007} }. Notation and preliminaries on Gaussian random variables. Generic examples-long-range dependence and smoothness. Other useful Gaussian source models. Applicability of Gaussian source models for network traffic. 3 Gaussian sources: validation, justification. Michel Mandjes.

бесплатно, без регистрации и без смс. In recent years the significance of Gaussian processes to communication networks has grown considerably.

Start by marking Large Deviations for Gaussian Queues: Modelling . The inherent flexibility of the Gaussian traffic model enables the analysis of both long-range and short-range dependent models in a single framework.

Start by marking Large Deviations for Gaussian Queues: Modelling Communication Networks as Want to Read: Want to Read savin. ant to Read.

Large Deviations for Gaussian Queues assumes minimal prior knowledge. We consider a queue fed by Gaussian traffic and give conditions on the input process under which the path space large deviations of the queue are governed by the rate function of the fractional Brownian motion.

Автор: Mandjes, Michel Название: Large deviations for gaussian queues Издательство . Modelling communication networks. Large Deviations for Gaussian Queues: Modelling Communication Networks. Category: Mathematics, Probability, Stochastic processes. 0 Mb. Category: science books, math.

Large Deviations for Gaussian Queues demonstrates how theGaussian traffic model arises naturally, and how the analysis ofthe corresponding queuing model can be performed. The text providesa general introduction to Gaussian queues, and surveys recentresearch into the modelling of communications networks. Coverageincludes:

Discussion of the theoretical concepts and practical aspectsrelated to Gaussian traffic models.Analysis of recent research asymptotic results for Gaussianqueues, both in the large-buffer and many-sources regime.An emphasis on rare-event analysis, relying on a variety ofasymptotic techniques.Examination of single-node FIFO queuing systems, as well asqueues operating under more complex scheduling disciplines, andqueuing networks.A set of illustrative examples that directly relate toimportant practical problems in communication networking.A large collection of instructive exercises and accompanyingsolutions.

Large Deviations for Gaussian Queues assumes minimalprior knowledge. It is ideally suited for postgraduate students inapplied probability, operations research, computer science andelectrical engineering. The book’s self-contained style makesit perfect for practitioners in the communications networkingindustry and for researchers in related areas.