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Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima and José Roberto de Almeida Amazonas ; cover design by Fernando Freitas
Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima and José Roberto de Almeida Amazonas ; cover design by Fernando Freitas
Autore de Lima Alexandre Barbosa
Pubbl/distr/stampa Aalborg, Denmark : , : River Publishers, , 2013
Descrizione fisica 1 online resource (186 p.)
Disciplina 621.3851
Collana River Publishers Series in Information Science and Technology
Soggetto topico Telecommunication - Traffic
Soggetto genere / forma Electronic books.
ISBN 87-92982-94-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ""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""; ""2.3.1 Exact second order self-similarity""; ""2.3.2 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""; ""3.6 Some H and d estimation methods""; ""3.6.1 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 andVeitch�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""; ""4.4 Prediction empirical studywith theTARFIMAmodel""; ""4.4.1 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""
Record Nr. UNINA-9910464482503321
de Lima Alexandre Barbosa  
Aalborg, Denmark : , : River Publishers, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima, Jose Roberto de Almeida Amazonas
Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima, Jose Roberto de Almeida Amazonas
Autore Lima Alexandre Barbosa De
Pubbl/distr/stampa Gistrup, Denmark : , : River Publishers, , [2013]
Descrizione fisica 1 online resource (186 p.)
Disciplina 621.3851
Collana River Publishers Series in Information Science and Technology
Soggetto topico Telecommunication - Traffic
ISBN 1-00-333866-6
1-003-33866-6
1-000-79238-2
87-92982-94-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ""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""; ""2.3.1 Exact second order self-similarity""; ""2.3.2 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""; ""3.6 Some H and d estimation methods""; ""3.6.1 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 andVeitch�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""; ""4.4 Prediction empirical studywith theTARFIMAmodel""; ""4.4.1 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""
Record Nr. UNINA-9910789376803321
Lima Alexandre Barbosa De  
Gistrup, Denmark : , : River Publishers, , [2013]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima, Jose Roberto de Almeida Amazonas
Internet teletraffic modeling and estimation / / Alexandre Barbosa de Lima, Jose Roberto de Almeida Amazonas
Autore Lima Alexandre Barbosa De
Pubbl/distr/stampa Gistrup, Denmark : , : River Publishers, , [2013]
Descrizione fisica 1 online resource (186 p.)
Disciplina 621.3851
Collana River Publishers Series in Information Science and Technology
Soggetto topico Telecommunication - Traffic
ISBN 1-00-333866-6
1-003-33866-6
1-000-79238-2
87-92982-94-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ""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""; ""2.3.1 Exact second order self-similarity""; ""2.3.2 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""; ""3.6 Some H and d estimation methods""; ""3.6.1 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 andVeitch�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""; ""4.4 Prediction empirical studywith theTARFIMAmodel""; ""4.4.1 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""
Record Nr. UNINA-9910825357203321
Lima Alexandre Barbosa De  
Gistrup, Denmark : , : River Publishers, , [2013]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui