## Computer Networks and Systems: Queueing Theory and Performance EvaluationStatistical performance evaluation has assumed an increasing amount of importance as we seek to design more and more sophisticated communication and information processing systems. The ability to predict a proposed system's per formance before one constructs it is an extremely cost effective design tool. This book is meant to be a first-year graduate level introduction to the field of statistical performance evaluation. It is intended for people who work with sta tistical performance evaluation including engineers, computer scientists and applied mathematicians. As such, it covers continuous time queueing theory (chapters 1-4), stochastic Petri networks (chapter 5), discrete time queueing theory (chapter 6) and recent network traffic modeling work (chapter 7). There is a short appendix at the end of the book that reviews basic probability theory. This material can be taught as a complete semester long course in performance evalua tion or queueing theory. Alternatively, one may teach only chapters 2 and 6 in the first half of an introductory computer networking course, as is done at Stony Brook. The second half of the course could use a more protocol oriented text such as ones by Saadawi [SAAD] or Stallings [STALl What is new in the third edition of this book? In addition to the well received material of the second edition, this edition has three major new features. |

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### Contents

I | 1 |

II | 2 |

III | 6 |

IV | 9 |

V | 11 |

VI | 13 |

VII | 19 |

VIII | 20 |

LXXIII | 219 |

LXXIV | 220 |

LXXV | 223 |

LXXVII | 224 |

LXXVIII | 226 |

LXXIX | 228 |

LXXX | 230 |

LXXXI | 232 |

IX | 22 |

X | 25 |

XI | 27 |

XII | 28 |

XIII | 29 |

XIV | 30 |

XV | 32 |

XVI | 37 |

XVII | 43 |

XVIII | 47 |

XIX | 48 |

XX | 51 |

XXI | 53 |

XXII | 55 |

XXIII | 56 |

XXIV | 59 |

XXV | 61 |

XXVI | 64 |

XXVII | 65 |

XXVIII | 68 |

XXIX | 69 |

XXX | 72 |

XXXI | 74 |

XXXII | 83 |

XXXIII | 85 |

XXXIV | 89 |

XXXV | 91 |

XXXVI | 92 |

XXXVII | 101 |

XXXVIII | 102 |

XXXIX | 103 |

XL | 104 |

XLI | 108 |

XLIII | 111 |

XLIV | 112 |

XLV | 118 |

XLVI | 130 |

XLVII | 132 |

XLVIII | 135 |

XLIX | 141 |

LI | 142 |

LII | 147 |

LIII | 148 |

LIV | 155 |

LV | 156 |

LVI | 163 |

LVII | 164 |

LVIII | 166 |

LIX | 170 |

LX | 197 |

LXII | 202 |

LXIII | 203 |

LXIV | 206 |

LXV | 207 |

LXVI | 208 |

LXVII | 211 |

LXVIII | 212 |

LXX | 214 |

LXXI | 216 |

LXXII | 218 |

LXXXII | 237 |

LXXXIII | 238 |

LXXXIV | 243 |

LXXXV | 249 |

LXXXVI | 251 |

LXXXVII | 253 |

LXXXVIII | 256 |

LXXXIX | 257 |

XC | 263 |

XCI | 268 |

XCII | 269 |

XCIII | 270 |

XCIV | 275 |

XCV | 276 |

XCVI | 280 |

XCVII | 282 |

XCVIII | 284 |

XCIX | 288 |

C | 290 |

CI | 294 |

CII | 297 |

CIII | 300 |

CIV | 303 |

CV | 308 |

CVI | 309 |

CVII | 310 |

CVIII | 312 |

CIX | 315 |

CX | 319 |

CXI | 320 |

CXII | 333 |

CXIII | 334 |

CXV | 336 |

CXVII | 337 |

CXX | 338 |

CXXIV | 339 |

CXXVIII | 340 |

CXXX | 341 |

CXXXIII | 342 |

CXXXVII | 343 |

CXL | 344 |

CXLII | 346 |

CXLIII | 347 |

CXLV | 348 |

CXLVII | 350 |

CXLVIII | 352 |

CXLIX | 353 |

CLI | 354 |

CLII | 355 |

CLIII | 357 |

CLIV | 358 |

CLV | 360 |

CLVI | 361 |

CLVII | 362 |

CLVIII | 363 |

CLXI | 365 |

CLXII | 403 |

405 | |

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### Common terms and phrases

analysis arrival process arrival rate Bernoulli process binomial distribution building blocks bursty calculate chapter Consider consists convolution algorithm corresponds customer leaving cyclic flows departure instant diagram of Figure equilibrium probabilities equilibrium state probabilities erasure nodes example exponential expression FIFO finite buffer four customers function global balance equation IEEE independent input queues KLEI 75 Little's Law M/M/l queueing system Markov chain mean number mean throughput modulating moment-generating function multiprocessor normalization constants number of arrivals number of customers number of packets output packet arrival packet switch parameter performance measures Petri Net Petri Nets Poisson process positive customers probability flux problem processor product form solution protocol queue length queueing model queueing theory random variables recursive RESOURCES place self-similar server service rate simulation slot solve star coupler state-dependent station statistics switching element task sequence techniques theorem third queue tion traffic equations transition diagram waiting

### References to this book

Vacation Queueing Models: Theory and Applications Naishuo Tian,Zhe George Zhang No preview available - 2006 |