LEADER 01066nam0 22002651i 450 001 SUN0047693 005 20060713120000.0 010 $a07-923340-7-8 100 $a20060713d1995 |0engc50 ba 101 $aeng 102 $aNL 105 $a|||| ||||| 200 1 $aComputational geomechanics$fArnold Verruijt 210 $aDordrecht$cKluwer$d1995 215 $aVIII, 383 p.$cill.$d25 cm$e1 floppy disk. 410 1$1001SUN0045251$12001 $aTheory and applications of transport in porous media$v7$1210 $aDordrecht$cKluwer. 620 $aNL$dDordrecht$3SUNL000068 700 1$aVerruijt$b, Arnold$3SUNV037913$0441065 712 $aKluwer$3SUNV000231$4650 801 $aIT$bSOL$c20181109$gRICA 912 $aSUN0047693 950 $aUFFICIO DI BIBLIOTECA DEI DIPARTIMENTI DI INGEGNERIA$d05 CONS G IV 053 $e05 1118 995 $aUFFICIO DI BIBLIOTECA DEI DIPARTIMENTI DI INGEGNERIA$bIT-CE0100$h1118$kCONS G IV 053$oc$qa 996 $aComputational geomechanics$91426752 997 $aUNICAMPANIA LEADER 04618nam 2200649 450 001 9910825357203321 005 20231206212927.0 010 $a1-00-333866-6 010 $a1-003-33866-6 010 $a1-000-79238-2 010 $a87-92982-94-8 035 $a(CKB)3710000000094832 035 $a(EBL)3400139 035 $a(SSID)ssj0001328305 035 $a(PQKBManifestationID)12414905 035 $a(PQKBTitleCode)TC0001328305 035 $a(PQKBWorkID)11283916 035 $a(PQKB)10764318 035 $a(Au-PeEL)EBL3400139 035 $a(CaPaEBR)ebr10852715 035 $a(OCoLC)878145315 035 $a(Au-PeEL)EBL7099440 035 $a(MiAaPQ)EBC3400139 035 $a(MiAaPQ)EBC7099440 035 $a(EXLCZ)993710000000094832 100 $a20230222d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aInternet teletraffic modeling and estimation /$fAlexandre Barbosa de Lima, Jose Roberto de Almeida Amazonas 210 1$aGistrup, Denmark :$cRiver Publishers,$d[2013] 210 4$dİ2013 215 $a1 online resource (186 p.) 225 0 $aRiver Publishers Series in Information Science and Technology 300 $aDescription based upon print version of record. 311 $a87-92982-10-7 320 $aIncludes bibliographical references and index. 327 $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"" 327 $a""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"" 327 $a""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 Whittlea???s method""; ""3.6.5 Haslett and Rafterya???s MV approximate estimator""; ""3.6.6 Abry andVeitcha???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"" 327 $a""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"" 327 $a""5.2.3 Empirical prediction with the TARFIMA model""""6 Conclusions""; ""Bibliography""; ""Index""; ""About the Authors"" 330 $aThis 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. 606 $aTelecommunication$xTraffic 615 0$aTelecommunication$xTraffic. 676 $a621.3851 700 $aLima$b Alexandre Barbosa De$01625680 702 $aAmazonas$b Jose? Roberto de Almeida 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910825357203321 996 $aInternet teletraffic modeling and estimation$93961314 997 $aUNINA