| Summary: | 碩士 === 國立清華大學 === 電機工程學研究所 === 86 ===
In general, high-speed network traffic is a complex, nonlinear, nonstationary process and significantly affected by unmeasurable parameters and variables. Thus a precise model of the process becomes increasingly difficult to proceed as the complexity of the process increases. Recently, fuzzy model is found to be a powerful method to discribe a real complex process with its nonlinear and time-varying properties. In this study, a fuzzy autoregressive (Fuzzy-AR) model is proposed to describe the traffic characteristics of high-speed networks.
The Fuzzy-AR model approximates a nonlinear time-variant process with a combination of several linear AR process via fuzzy clustering method. We advocate the use of Fuzzy-AR model because of its flexibility in capturing the traffic characteristics at different high speed network's structures. Furthermore, the Fuzzy-AR model is more suitable for the development of congestion control scheme of packet network traffic. A parameter estimation problem of Fuzzy-AR modeling is treated by a clustering algorithm from actual traffic data in networks. Finally, based on the packet traffics on Ethernet-LAN network in Bellcore, several illustrative examples are given to demonstrate the validity of the proposed Fuzzy-AR model in high speed network traffic.
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