| 000 | 05881nam a2200733 i 4500 | ||
|---|---|---|---|
| 001 | 6813292 | ||
| 003 | IEEE | ||
| 005 | 20220822104830.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 121210s2012 caua foab 000 0 eng d | ||
| 020 | _a9781598292695 (electronic bk.) | ||
| 020 | _z9781598292688 (pbk.) | ||
| 024 | 7 |
_a10.2200/S00454ED1V01Y201210COM008 _2doi |
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| 035 | _a(CaBNVSL)swl00401757 | ||
| 035 | _a(OCoLC)820720069 | ||
| 040 |
_aCaBNVSL _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aT57.9 _b.T727 2012 |
|
| 082 | 0 | 4 |
_a519.82 _223 |
| 100 | 1 | _aTranter, William H. | |
| 245 | 1 | 2 |
_aA tutorial on queuing and trunking with applications to communications _h[electronic resource] / _cWilliam H. Tranter and Allen B. MacKenzie. |
| 260 |
_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _cc2012. |
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| 300 |
_a1 electronic text (xii, 92 p.) : _bill., digital file. |
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| 490 | 1 |
_aSynthesis lectures on communications, _x1932-1708 ; _v# 8 |
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| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Adobe Acrobat Reader. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 500 | _aSeries from website. | ||
| 504 | _aIncludes bibliographical references (p. 89-90). | ||
| 505 | 0 | _a1. Introduction -- 1.1 The Poisson process - strengths and weaknesses -- 1.2 Outline -- 1.3 MATLAB -- | |
| 505 | 8 | _a2. Poisson, Erlang, and Pareto distributions -- 2.1 The Poisson distribution -- 2.1.1 Development of the Poisson distribution -- 2.1.2 Interevent times -- 2.2 The Erlang distribution -- 2.2.1 Derivation of the Erlang distribution -- 2.2.2 Mean and variance of the Erlang-m random variable -- 2.2.3 Plots of the Erlang distribution -- 2.2.4 Erlang and gamma random variables -- 2.3 The Pareto distribution -- 2.4 Problems -- 2.5 Appendix A. Generating samples with an exponential distribution -- 2.6 Appendix B. The gamma function -- | |
| 505 | 8 | _a3. A brief introduction to queueing theory -- 3.1 Birth-death processes -- 3.2 Examples of simple queues -- 3.2.1 The single-server queue -- 3.2.2 Multiple-server queues -- 3.3 Three example simulations -- 3.3.1 The simulation of a pure birth process -- 3.3.2 Simulation of a birth-death process -- 3.4 Problems -- 3.5 Appendix A. The moment-generating function -- 3.6 Appendix B. MATLAB code for examples 3.2 and 3.3 -- 3.6.1 MATLAB code for example 3.2 -- 3.6.2 MATLAB code for example 3.3 -- | |
| 505 | 8 | _a4. Blocking and delay -- 4.1 Erlang-B results (M/M/C/C) -- 4.2 Erlang-C results (M/M/C/[infinity]) -- 4.3 Delay time, Little's theorem -- 4.3.1 Little's theorem -- 4.3.2 Average queue length for M/M/C/[infinity] system -- 4.3.3 Result for delay -- 4.4 Problems -- 4.5 Appendix A. MATLAB code for the Erlang-B chart -- 4.6 Appendix B. MATLAB code for the Erlang-C chart -- | |
| 505 | 8 | _a5. Networks of queues -- 5.1 Burke's theorem -- 5.2 Basic model -- 5.3 Jackson's theorem -- 5.3.1 Statement of Jackson's theorem -- 5.3.2 Proof of Jackson's theorem -- 5.4 Extensions to Jackson's theorem -- 5.4.1 Dependent service rate networks -- 5.4.2 Jackson's theorem for dependent service rate network -- 5.4.3 Closed networks -- 5.4.4 Jackson's theorem for closed networks -- 5.5 BCMP theorem -- 5.5.1 Statement of the BCMP theorem -- 5.6 Kleinrock's formula -- 5.7 Problems -- 5.8 Appendix A. MATLAB code for example 5.3 -- 5.9 Appendix B. MATLAB code for example 5.3 -- | |
| 505 | 8 | _aBibliography -- Authors' biographies. | |
| 506 | 1 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | |
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _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 are the 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. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF t.p. (viewed on December 10, 2012). | ||
| 630 | 0 | 0 | _aMATLAB. |
| 650 | 0 |
_aQueuing networks (Data transmission) _xMathematical models. |
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| 650 | 0 | _aQueuing theory. | |
| 653 | _aqueuing | ||
| 653 | _atrunking | ||
| 653 | _aPoisson process | ||
| 653 | _aErlang distribution | ||
| 653 | _aErlang-A and Erlang-B characteristics | ||
| 653 | _ablocking probability | ||
| 653 | _adelay probability | ||
| 653 | _aLittle's theorem | ||
| 653 | _anetworks of queues | ||
| 653 | _aJackson's theorem | ||
| 653 | _aBCMP theorem | ||
| 653 | _aKleinrock's formula | ||
| 700 | 1 |
_aMacKenzie, Allen Brantley, _d1977- |
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| 776 | 0 | 8 |
_iPrint version: _z9781598292688 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on communications ; _v# 8. _x1932-1708 |
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| 856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813292 |
| 999 |
_c237956 _d237956 |
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