Unicast inference of network link delay distributions from edge measurements

Inference of network internal link characteristics has become an increasingly important issue for operating and evaluating large telecommunication networks. Since it is usually impractical to directly monitor each link along a specific path, end-to-end probes are sometimes used to collect link characteristic information at edge nodes of the network. This paper deals with unicast probing methods for estimation of link delay characteristics. Unicast traffic is easy to generate and is supported by almost every network currently in operation. Under the assumptions that link delays are spatially and temporally independent, we propose a bias corrected estimator for the internal link delay cumulant generating function (CGF) based on unicast probe end-to-end delay measurements. Through simulation we show that the proposed estimator attains a level of mean squared error comparable to link delay CGF estimates obtained from directly measured link delay statistics. We can use these CGF estimates to estimate delay mean, variance and level exceedance probabilities for each link.