| 基于LFSN自相似流量模型的随机突发边界分析 |
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| 引用本文： | 喻莉,白云,朱光喜.基于LFSN自相似流量模型的随机突发边界分析[J].通信学报,2010,31(5):16-21. |
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| 作者姓名： | 喻莉 白云 朱光喜 |
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| 作者单位： | 华中科技大学,武汉光电国家实验室,湖北,武汉,430074 |
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| 基金项目： | 国家自然科学基金，教育部新世纪优秀人才支持计划，国家高技术研究发展计划("863"计划)基金资助项目，国家实验室基金资助项目 |
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| 摘 要： | 基于线形分形稳定噪声(LFSN)的网络业务流模型可以很好地描述流量的自相似和重尾特性,对这种模型的随机突发边界进行理论推导,得出较现有文献更为普遍的结论,尤其是其随机上界更为精确,因此在随机网络演算分析中有着重要意义.同时基于对一般LFSN过程的快速模拟,设计了一种独特的实验方法,得到突发边界随机分布的估计值,验证了理论推导的正确性.
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| 关 键 词： | 随机突发边界 自相似 随机网络演算 性能分析 线性分形稳定噪声 |
Stochastic burstiness boundary analysis of LFSN-based self-similar network traffic model |
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| YU Li,BAI Yun,ZHU Guang-xi.Stochastic burstiness boundary analysis of LFSN-based self-similar network traffic model[J].Journal on Communications,2010,31(5):16-21. |
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| Authors: | YU Li BAI Yun ZHU Guang-xi |
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| Affiliation: | YU Li,BAI Yun,ZHU Guang-xi (Wuhan National Laboratory for Optoelectronics,Huazhong Science & Technology University,Wuhan 430074,China) |
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| Abstract: | A stochastic burstiness boundary of general LFSN(linear fractional stable noise)-based traffic model,which is an important model that has been proven capable to capture both properties of self-similar and heavy tailed,was derived.The final result is much more general than the current one,especially for the upper boundary which is also more accurate.Meanwhile,a unique experiment based on fast simulation of general LFSN process was set up to get an estimation result for actual distribution,which in turn prove... |
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| Keywords: | stochastic burstiness boundary self-similar stochastic network calculus performance analysis linear fractional stable noise |
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