Network Loss Inference With Second Order Statistics of End-to-End Flows

The authors address the problem of calculating link loss rates from end-to-end measurements. Contrary to existing works that use only the average end-to-end loss rates or strict temporal correlations between probes, the authors exploit second-order moments of end-to-end flows. They first prove that the variances of link loss rates can be uniquely calculated from the covariance's of the measured end-to-end loss rates in any realistic topology. After calculating the link variances, they remove the un-congested links with small variances from the first-order moment equations to obtain a full rank linear system of equations, from which we can calculate precisely the loss rates of the remaining congested links.