Faculty Candidate Seminar: Statistical Inference for Network Tomography

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Abstract: We study network tomography questions, which are large scale inverse
inference problems and vital for many network traffic engineering tasks such as
dynamic routing optimization, Quality of Service (QoS) guarantee. We propose a
pseudo likelihood approach for estimating parameters of these problems based on
the principle of divide-and-conquer. The example of multicast link delay
estimation problem is used to motivate the concept. We then apply the pseudo
likelihood approach to the problem of estimating origin-destination matrix
through link traffic counts, which is one of the core problems in network
traffic engineering.

This is joint work with Bin Yu.


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  • Created By:
    Barbara Christopher
  • Created:
  • Modified By:
    Fletcher Moore
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