000			03973nam a22004215i 4500
999			_c387183 _d387183
001			387183
003			ES-MaUEC
005			20230212132926.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			220601s2012 sz | s |||| 0|eng d
020			_a9783031016790
024	7		_a10.1007/978-3-031-01679-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aT57.9 _b2012 EB
100	1		_aTranter, William H. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686788
245	1	2	_aA Tutorial on Queuing and Trunking with Applications to Communications _cby William Tranter, Allen B. MacKenzie
250			_a1st edition 2012
264		1	_aCham _bSpringer International Publishing _c2012
300			_a1 recurso en línea (XII, 92 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Communications _x1932-1708
505	0		_aIntroduction -- Poisson, Erlang, and Pareto Distributions -- A Brief Introduction to Queueing Theory -- Blocking and Delay -- Networks of Queues.
520			_aThe motivation for developing this synthesis lecture was to provide a tutorial on queuing and trunking, with extensions to networks of queues, suitable for supplementing courses in communications, stochastic processes, and networking. An essential component of this lecture is MATLAB-based demonstrations and exercises, which can be easily modified to enable the student to observe and evaluate the impact of changing parameters, arrival and departure statistics, queuing disciplines, the number of servers, and other important aspects of the underlying system model. Much of the work in this lecture is based on Poisson statistics, since Poisson models are useful due to the fact that Poisson models are analytically tractable and provide a useful approximation for many applications. We recognize that the validity of Poisson statistics is questionable for a number of networking applications and therefore we briefly discuss self-similar models and the Hurst parameter, long-term dependent models, the Pareto distribution, and other related topics. Appropriate references are given for continued study on these topics. The initial chapters of this book consider individual queues in isolation. The systems studied consist of an arrival process, a single queue with a particular queuing discipline, and one or more servers. While this allows us to study the basic concepts of queuing and trunking, modern data networks consist of many queues that interact in complex ways. While many of these interactions defy analysis, the final chapter introduces a model of a network of queues in which, after being served in one queue, customers may join another queue. The key result for this model is known as Jackson's Theorem. Finally, we state the BCMP Theorem, which can be viewed as a further extension of Jackson's Theorem and present Kleinrock's formula, which can be viewed as the network version of Little's Theorem. Table of Contents: Introduction / Poisson, Erlang, and Pareto Distributions / A Brief Introduction to Queueing Theory / Blocking and Delay / Networks of Queues.
988			_aSynthesis Collection of Technology_2012
630	0	0	_9683084 _aMATLAB (Archivo de ordenador)
650		7	_2embne _9665538 _aColas de espera, Teoría de
700	1		_aMacKenzie, Allen Brantley, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686781 _d1977-
776	0	8	_iPrinted edition: _z9783031005510
776	0	8	_iPrinted edition: _z9783031028076
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01679-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI