Performance Modeling, Stochastic Networks, and Statistical Multiplexing, Second Edition - Mazumdar, Ravi R.
42,79 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
0 °P sammeln
  • Broschiertes Buch

This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in computing performance measures. The monograph also covers stochastic network theory including Markovian networks. Recent results on network utility optimization and connections to stochastic insensitivity are discussed. Also presented are ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. In particular, the important concept of effective bandwidths as mappings from queueing level phenomena to loss network models is clearly presented along with a detailed discussion of accurate approximations for large networks.
Autorenporträt
Ravi R. Mazumdar was born in 1955 in Bangalore, India. He was educated at the Indian Institute of Technology, Bombay (B.Tech. 1977), Imperial College, London, UK (MSc, DC 1978), and received his PhD from the University of California, Los Angeles (UCLA) in 1983. He was an Assistant Professor of Electrical Engineering at Columbia University, NY (1985-88); Associate and Full Professor at the Institut National de la Recherche Scientifique, Montreal, Canada (1988-97). From 1996-2000 he held the Chair in Operational Research at the University of Essex, Colchester, UK, and from 1999-2005 was Professor of ECE at Purdue University, West Lafayette, USA. Since Fall 2004 he has been with the Department of Electrical and Computer Engineering at the University of Waterloo, Canada as a University Research Chair Professor. Dr. Mazumdar is a Fellow of the IEEE and the Royal Statistical Society. He was a recipient of the IEEE INFOCOM Best Paper Award in 2006 and was Runner-up for the Best Paper at the INFOCOM in 1998. His research interests are in stochastic modeling and analysis with applications to wireline and wireless networks; in game theory and its applications to networking; and in stochastic analysis and queueing theory.