  Packet-dispersion based measurement tools insert pairs of probe packets with
a known separation into the network for transmission over a unicast path or a
multicast tree. Samples of the separation between the probe pairs at the
destination(s) are observed. Heuristic techniques are then used by these tools
to estimate the path characteristics from the observations. In this paper we
present a queueing theoretic setting for packet-dispersion based probing.
Analogous to network tomography, we develop techniques to estimate the
parameters of the arrival process to the individual links from the samples of
the output separations, i.e., from the end-to-end measurements. The links are
modeled as independent discrete time queues with i.i.d. arrivals. We first
obtain an algorithm to obtain the (joint) distribution of the separation
between the probes at the destination(s) for a given distribution of the
spacing at the input. The parameter estimates of the arrival process are
obtained as the minimizer of a cost function between the empirical and
calculated distributions. We also carry out extensive simulations and numerical
experiments to study the performance of the estimation algorithm under the
fairly `harsh' conditions of non stationarity of the arrival process. We find
that the estimations work fairly well for two queues in series and for
multicast.
