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- W2907046879 abstract "This project is to generate the self-similar network traffic. It is generally acceptedthat self-similar or fractal process may provide better models for in modern networktraffic than Poisson process. Poisson arrival processes are not self-similar, regardlessof degree of aggregation. The way to solve this problem, we applied the existedmethod in visual C++ programming with used the Random midpoint Displacement(RMD) algorithm. That program we need the sequence of the random number as adata. The data was generated depends on the power of two of data. The numbers ofdata will be analyzed using the R/S Statistic program and Variance Time Plotprogram. That analysis programs were running in MathCAD v12 platform. The graftwill be display after the data is running in the analysis programs as result. The newvalues of Hurst will be appear as a results whether the self-similar or not. After theanalysis process, the result from the R/S Statistic and Variance Tome Plot were notaccurate. The new value of Hurst was not exactly same with the expected value ofHurst. As a conclusion, using RMD algorithm the result are more satisfy compareusing the traditional process because the result are more accurate are more faster.The RMD fastest in term of computational time but do not accurately reflect theHurst parameter." @default.
- W2907046879 created "2019-01-11" @default.
- W2907046879 creator A5072905724 @default.
- W2907046879 date "2006-01-01" @default.
- W2907046879 modified "2023-09-23" @default.
- W2907046879 title "Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini" @default.
- W2907046879 hasPublicationYear "2006" @default.
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