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dc.contributorGuu-Chang Yangen_US
dc.contributorChein-I Changen_US
dc.contributor.advisorYen-Chieh Ouyangen_US
dc.contributor.authorLiu, Shin-Tzeen_US
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dc.description.abstractNetwork devices put packets on an internet link, and multiplex, or superimpose the packet form different active connections. Network arrivals are often modeled as Poisson processes for analytic simplicity, even thought a number of traffic studies have shown that packet inter-arrivals are not exponentially distribution. The notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In recent years, many researchers reexamine the Poisson distribution model for traffic assumption and they point out that once the connection load is sufficiently large, the network begins pushing back on the attraction to Poisson and independence by causing queueing on the link-input router. Therefore, performance analysis of queueing system in long-range dependence traffic is needed to design a reliable network under the tremendous growth of internet traffic. In this thesis, we use a synthesize inter-arrival time distribution form ARIMA model and measure the sensitivity of output performance under various degrees of long-range dependent packet arrival. Experimental results show that packet arrival processes appear better modeled as self-similar processes.en_US
dc.description.tableofcontents致謝 i 摘要 ii Abstract iii 1. Introduction 1 1.1 Motivation 1 1.2 Overview of Internet Traffic 3 1.3 Contribution and Organization of Thesis 7 2. Self-similar process 8 2.1 Definition of self-similar process 9 2.2 Fractional Brownian motion 11 2.3 Characteristic of self-similar process 12 2.4 Simple linear regression 16 2.6 Autoregressive, Integrative and Moving-Average (ARIMA) model 22 2.7 Summary 27 3. Discrete Wavelet Transform and Multiresolution Analysis 28 3.1 Definition of Discrete Wavelet Transform 29 3.2 Multiresolution Analysis (MRA) 32 3.3 Vanishing Wavelet Moments 36 3.4 Summary 38 4. Wavelet-based Analysis of Long-Range-Dependence 39 4.1 The Long-Range Dependence Phenomenon 40 4.3 Wavelet Transform of Long-range dependence process 41 4.2 The estimator of Long-Range Dependence 42 4.3 Two Key Properties in the Scaling Processes 45 4.5 Wavelet-based analysis compare with traditional estimator 49 4.6 Summary 50 5. Queueing System Output Performance with Self-similar Input 51 5.1 The Single-Server Queue 52 5.2 Birth-Death Process 53 5.3 Lindley’s Integral Equation 56 5.4 Two Parameter for the Synthesize Traffic 62 5.5 Simulation Result with Single Synthesize Trace 64 5.6 Simulation Result with Real traffic 70 5.7 The G/G/1 queueing superimposition 73 6. Conclusions and Future works 87 6.1 Conclusions 87 6.2 Future works 88 7. Reference 89zh_TW
dc.subjectWavelet-based analysisen_US
dc.subjectInter-arrival timeen_US
dc.subjectPacket sizeen_US
dc.titleThe Self-Similarity Measurement for Internet Traffic based on Wavelet-analysis in G/G/1 Queueing Systemen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextno fulltext-
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