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Scalable estimation of multicast session characteristics
So that Internet multicast sessions can reach thousands, or even millions, of participants, rather than the tens they reach today, we need new techniques for estimating important session management parameters. These parameters include the number of participants in a multicast session, the topology of the multicast tree, and the loss rates along links in the tree. Such parameters can be used by adaptive algorithms for improved data transmission. For example, forward error correction for lost multicast packets can be tuned to the number of participants, and participants can use topology and loss rate information to help identify fellow participants that are well situated to retransmit multicast packets that have been lost and cannot be reconstituted. New techniques are needed in order to avoid the feedback implosion that results from querying all participants. For example, in estimating the session size, one approach is to count all participants individually. For large session sizes, a more scalable approach is to poll to obtain responses from some fraction of the participants and then estimate the session size based upon the sample of responses received. Likewise, in traces of data packet receipts and losses to estimate topology and loss rates, collecting all available traces from all participants can consume more bandwidth than is used by the original data packets. A more scalable approach is to thin the traces, or to select only a subset of the traces and limit one's estimation goal to identifying only the lossiest links in the multicast tree. The bandwidth savings from restricting feedback comes at a cost in estimation quality. Our interest is in devising techniques that can deliver a satisfactory trade-off for envisioned application requirements. An important part of this task is to characterize the trade-off in precise terms that will allow an application to intelligently choose its own operating point. We propose scaling solutions to three multicast session parameter estimation problems. These are the estimation of session size, of multicast distribution tree topology, and of the location of the lossiest links in a tree.
Friedman, Timur, "Scalable estimation of multicast session characteristics" (2002). Doctoral Dissertations Available from Proquest. AAI3056225.