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020 _a9783031016790
_9978-3-031-01679-0
024 7 _a10.1007/978-3-031-01679-0
_2doi
050 4 _aT1-995
072 7 _aTBC
_2bicssc
072 7 _aTEC000000
_2bisacsh
072 7 _aTBC
_2thema
082 0 4 _a620
_223
100 1 _aTranter, William.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_985133
245 1 2 _aA Tutorial on Queuing and Trunking with Applications to Communications
_h[electronic resource] /
_cby William Tranter, Allen B. MacKenzie.
250 _a1st ed. 2012.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2012.
300 _aXII, 92 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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 versionof Little's Theorem. Table of Contents: Introduction / Poisson, Erlang, and Pareto Distributions / A Brief Introduction to Queueing Theory / Blocking and Delay / Networks of Queues.
650 0 _aEngineering.
_99405
650 0 _aElectrical engineering.
_985135
650 0 _aTelecommunication.
_910437
650 1 4 _aTechnology and Engineering.
_985137
650 2 4 _aElectrical and Electronic Engineering.
_985139
650 2 4 _aCommunications Engineering, Networks.
_931570
700 1 _aMacKenzie, Allen B.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_985142
710 2 _aSpringerLink (Online service)
_985144
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031005510
776 0 8 _iPrinted edition:
_z9783031028076
830 0 _aSynthesis Lectures on Communications,
_x1932-1708
_985146
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01679-0
912 _aZDB-2-SXSC
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999 _c85772
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