Cargando…
Internet teletraffic modeling and estimation /
This book presents a new statespace model for Internet traffic, which is based on a finite-dimensional representation of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) random process. The modeling via Autoregressive (AR) processes is also investigated.
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Aalborg, Denmark :
River Publishers,
2013.
|
| Colección: | River Publishers Series in Information Science and Technology
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_ocn878145315 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 140408t20132013dk a ob 001 0 eng d | ||
| 040 | |a E7B |b eng |e rda |e pn |c E7B |d OCLCQ |d OCLCO |d OCLCF |d OCLCQ |d YDXCP |d EBLCP |d DEBSZ |d BTCTA |d COCUF |d ZCU |d MERUC |d U3W |d STF |d OCLCQ |d EZ9 |d ICG |d VT2 |d AU@ |d OCLCQ |d TKN |d DKC |d OCLCQ |d UKAHL |d OCLCQ |d OCLCO |d YDX |d OCLCQ |d SFB |d OCLCQ |d OCLCO | ||
| 019 | |a 961593828 |a 962634121 | ||
| 020 | |a 9788792982940 |q (e-book) | ||
| 020 | |a 8792982948 |q (e-book) | ||
| 020 | |z 9788792982100 | ||
| 029 | 1 | |a AU@ |b 000057161026 | |
| 029 | 1 | |a DEBBG |b BV044056754 | |
| 029 | 1 | |a DEBSZ |b 449773582 | |
| 035 | |a (OCoLC)878145315 |z (OCoLC)961593828 |z (OCoLC)962634121 | ||
| 050 | 4 | |a TK5102.985 |b .D455 2013eb | |
| 082 | 0 | 4 | |a 621.3851 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a De Lima, Alexandre Barbosa, |e author. | |
| 245 | 1 | 0 | |a Internet teletraffic modeling and estimation / |c Alexandre Barbosa de Lima and José Roberto de Almeida Amazonas ; cover design by Fernando Freitas. |
| 264 | 1 | |a Aalborg, Denmark : |b River Publishers, |c 2013. | |
| 264 | 4 | |c ©2013 | |
| 300 | |a 1 online resource (187 pages) : |b illustrations, tables | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 0 | |a River Publishers Series in Information Science and Technology | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (ebrary, viewed April 7, 2014). | |
| 505 | 0 | |a Cover; Contents; List of Tables; List of Figures; Preface; List of acronyms and symbols; 1 Introduction; 1.1 Objectives of telecommunications carriers; 1.2 Traffic characteristics; 1.3 Questions and contributions; 1.4 Time series basic concepts; 1.4.1 Time series examples; 1.4.2 Operators notation; 1.4.3 Stochastic processes; 1.4.4 Time seriesmodeling; 2 The fractal nature of network traffic; 2.1 Fractals and self-similarity examples; 2.1.1 The Hurst exponent; 2.1.2 Samplemean variance; 2.2 Long range dependence; 2.2.1 Aggregate process; 2.3 Self-similarity. | |
| 505 | 8 | |a 2.3.1 Exact second order self-similarity2.3.2 Impulsiveness; 2.4 Final remarks: why is the data networks traffic fractal?; 3 Modeling of long-range dependent teletraffic; 3.1 Classes of modeling; 3.1.1 Non-parametric modeling; 3.2 Wavelet transform; 3.2.1 Multiresolution analysis and the discrete wavelet transform; 3.3 ModelMWM; 3.4 Parametric modeling; 3.4.1 ARFIMAmodel; 3.4.2 ARFIMA models prediction -- optimum estimation; 3.4.3 Formsof prediction; 3.4.4 Confidence interval; 3.4.5 ARFIMAprediction; 3.5 Longmemorystatistical tests; 3.5.1 R/Sstatistics; 3.5.2 GPHtest. | |
| 505 | 8 | |a 3.6 Some H and d estimation methods3.6.1 R/Sstatistics; 3.6.2 Variance plot; 3.6.3 Periodogram method; 3.6.4 Whittle's method; 3.6.5 Haslett and Raftery's MV approximate estimator; 3.6.6 Abry and Veitch'swavelet estimator; 3.7 Bi-spectrum and linearity test; 3.8 KPSS stationarity test; 4 State-space modeling; 4.1 Introduction; 4.2 TARFIMAmodel; 4.2.1 Multistep prediction with the Kalman filter; 4.2.2 The prediction power of the TARFIMA model; 4.3 Series exploratory analysis; 4.3.1 ARFIMA(0; 0.4; 0) series; 4.3.2 MWM series with H = 0.9; 4.3.3 Nile river series. | |
| 505 | 8 | |a 4.4 Prediction empirical studywith the TARFIMAmodel4.4.1 ARFIMA(0, d, 0) series; 4.4.2 MWMseries; 4.4.3 Nile river series between years 1007 and 1206; 4.4.4 Conclusions; 5 Modeling of Internet traffic; 5.1 Introduction; 5.2 Modeling of the UNC02 trace; 5.2.1 Exploratory analysis; 5.2.2 Long memory local analysis of the UNC02 trace; 5.2.3 Empirical prediction with the TARFIMA model; 6 Conclusions; Bibliography; Index; About the Authors. | |
| 520 | |a This book presents a new statespace model for Internet traffic, which is based on a finite-dimensional representation of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) random process. The modeling via Autoregressive (AR) processes is also investigated. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Telecommunication |x Traffic. | |
| 650 | 6 | |a Télécommunications |x Trafic. | |
| 650 | 7 | |a Telecommunication |x Traffic |2 fast | |
| 700 | 1 | |a Amazonas, José Roberto de Almeida, |e author. | |
| 700 | 1 | |a Freitas, Fernando, |e cover designer. | |
| 776 | 0 | 8 | |i Print version: |a De Lima, Alexandre Barbosa. |t Internet teletraffic modeling and estimation. |d Aalborg, Denmark : River Publishers, ©2013 |h xx, 165 pages |k River Publishers Series in Information Science and Technology. |z 9788792982100 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=3400139 |z Texto completo |
| 936 | |a BATCHLOAD | ||
| 938 | |a Askews and Holts Library Services |b ASKH |n AH25802363 | ||
| 938 | |a Baker and Taylor |b BTCP |n BK0020002519 | ||
| 938 | |a EBL - Ebook Library |b EBLB |n EBL3400139 | ||
| 938 | |a ebrary |b EBRY |n ebr10852715 | ||
| 938 | |a YBP Library Services |b YANK |n 303231153 | ||
| 938 | |a YBP Library Services |b YANK |n 18126464 | ||
| 938 | |a YBP Library Services |b YANK |n 11865589 | ||
| 994 | |a 92 |b IZTAP | ||