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Multiple source network tomography: a hypothesis-testing approach

机译:多源网络断层扫描:一种假设检验方法

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Summary form only given. Knowledge of internal network behaviour is of fundamental importance for a variety of problems such as routing optimization and anomaly detection. The problem of inferring network characteristics using end-to-end measurements is referred to as network tomography. This paper investigates the multiple-source, multiple-receiver (M-by-N) network tomography problem. We identify the dichotomy of 2-by-2 topology components and show that their consideration is sufficient for solving the general M-by-N problem. We describe a probing methodology and decompose the tomography problem into two stages: a series of generalized likelihood ratio tests that determine the appropriate data aggregation, followed by maximum likelihood estimation.
机译:仅提供摘要表格。内部网络行为的知识对于各种问题(如路由优化和异常检测)至关重要。使用端到端测量来推断网络特性的问题称为网络层析成像。本文研究了多源,多接收器(M-by-N)网络层析成像问题。我们确定了2×2拓扑组件的二分法,并表明它们的考虑足以解决一般的M×N问题。我们描述了一种探测方法,并将层析成像问题分解为两个阶段:一系列广义似然比测试,确定适当的数据聚合,然后进行最大似然估计。

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