Testing the Gaussian assumption for self-similar teletraffic models

S. Bates, S. McLaughlin
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引用次数: 14

Abstract

Both the fractional Brownian motion (fBm) and the autoregressive integrated moving average (ARIMA) models have been applied to teletraffic scenarios in recent years. These models became popular after the discovery that Ethernet and VBR video data appear to possess the property of self-similarity. However the results presented in this paper suggest that Ethernet data is more impulsive than traffic generated by these models.
检验自相似远程通信模型的高斯假设
分数阶布朗运动(fBm)和自回归积分移动平均(ARIMA)模型近年来在远程交通场景中得到了应用。这些模型是在发现以太网和VBR视频数据具有自相似的特性后流行起来的。然而,本文的结果表明,以太网数据比这些模型产生的流量更具冲动性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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