首页> 外文会议>Signal Acquisition and Processing, 2009. ICSAP 2009 >Predicting Traffic Bursts Using Extreme Value Theory
【24h】

Predicting Traffic Bursts Using Extreme Value Theory

机译:使用极值理论预测交通突发

获取原文

摘要

Traffic bursts appear to be more pronounced recently and have major consequences for network quality of service. We investigate the extreme behavior of bursts and quantify the probabilities of these large bursts. Taking Bellcore internal Ethernet traces as an example, we applied generalized extreme value model over block maxima. The analysis reveals that traffic burst maxima follows GEV model with negative shape parameter. Traffic bursts are in the domain of attraction of Weibull distribution. Our result confirms the conclusion of Norros of storage fed with Gaussian self-similar input.
机译:流量突发最近似乎更加明显,并且对网络服务质量产生了重大影响。我们调查突发的极端行为并量化这些大突发的概率。以Bellcore内部以太网跟踪为例,我们在块最大值上应用了广义极值模型。分析表明,交通突发最大值遵循具有负形状参数的GEV模型。交通突发是威布尔分布吸引的领域。我们的结果证实了以高斯自相似输入为输入的存储Norros的结论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号