Explicit Maximum Likelihood Loss Estimator in Multicast Tomography

Details Explicit Maximum Likelihood Loss Estimator in Multicast Tomography Explicit Maximum Likelihood Loss Estimator in Multicast Tomography

2010-04-27

arxiv.org/abs/1004.4690v1

Computer Science

Networking and Internet Architecture

submitted for publication

Scientific paper

For the tree topology, previous studies show the maximum likelihood estimate (MLE) of a link/path takes a polynomial form with a degree that is one less than the number of descendants connected to the link/path. Since then, the main concern is focused on searching for methods to solve the high degree polynomial without using iterative approximation. An explicit estimator based on the Law of Large Numbers has been proposed to speed up the estimation. However, the estimate obtained from the estimator is not a MLE. When $n<\infty$, the estimate may be noticeable different from the MLE. To overcome this, an explicit MLE estimator is presented in this paper and a comparison between the MLE estimator and the explicit estimator proposed previously is presented to unveil the insight of the MLE estimator and point out the pitfall of the previous one.

Affiliated with

Also associated with

No associations

Rating

Explicit Maximum Likelihood Loss Estimator in Multicast Tomography does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Explicit Maximum Likelihood Loss Estimator in Multicast Tomography, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Explicit Maximum Likelihood Loss Estimator in Multicast Tomography will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-236701