In this paper we consider the problem of inferring link-level loss rates from end-to-end multicast measurements taken from a collection of trees. We give conditions under which loss rates are identifiable on a specified set of links. Two algorithms are presented to perform the link-level inferences for those links on which losses can be identified. One, the minimum variance weighted average (MVWA) algorithm treats the trees separately and then averages the results. The second, based on expectation-maximization (EM) merges all of the measurements into one computation. Simulations show that EM is slightly more accurate than MVWA, most likely due to its more efficient use of the measurements. We also describe extensions to the inference of link-level delay, inference from end-to-end unicast measurements, and inference when some measurements are missing.
Tian Bu, Nick G. Duffield, Francesco Lo Presti, Do