摘要翻译:
本文介绍了一种基于网络中链路负载的一次快照观测估计网络流量矩阵的迭代tomogravity算法。所提出的方法不需要像现有的方法那样完全观察单个边缘链上的总载荷或适当地调整惩罚参数。数值结果表明,当链路数据完全观测时,迭代层析重力方法能很好地控制估计误差,并且在有中等数量缺失链路数据的情况下能产生鲁棒的结果。
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英文标题:
《An iterative tomogravity algorithm for the estimation of network traffic》
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作者:
Jiangang Fang, Yehuda Vardi, Cun-Hui Zhang
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最新提交年份:
2007
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分类信息:
一级分类:Statistics 统计学
二级分类:Applications 应用程序
分类描述:Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学,教育学,流行病学,工程学,环境科学,医学,物理科学,质量控制,社会科学
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英文摘要:
This paper introduces an iterative tomogravity algorithm for the estimation of a network traffic matrix based on one snapshot observation of the link loads in the network. The proposed method does not require complete observation of the total load on individual edge links or proper tuning of a penalty parameter as existing methods do. Numerical results are presented to demonstrate that the iterative tomogravity method controls the estimation error well when the link data is fully observed and produces robust results with moderate amount of missing link data.
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PDF链接:
https://arxiv.org/pdf/708.0945


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