THROUGHPUT ANALYSIS FOR CONGESTION CONTROL IN MULTICAST GROUPS

Abstract

Multicasting is sending a packet to a group of receivers on a network. The group of receivers associated with a class D address is referred to as a multicast group. Congestion controls for large multicastgroups is also a challenging problem, we can't apply end-to-end congestion control method and the congestion condition in different parts of a multicast tree are likely to be different and continuously changing. For this purpose, congestion feedback must be gathered from all receivers in scalable & periodic manner. In this project, the study for the impact of random queueing delays stemming from traffic variability on the performance of a multicast session was carried out. With a simple analytical model, the throughput degradation within a multicast (one-to-many) tree under TCP-like congestion and flow control was analyzed. The (max, plus) formalism together with methods based on stochastic comparison (association and convex ordering) and on the theory of extremes was used to prove various properties of the throuhput. We first prove that the throughput predicted by a deterministic model is systematically optimistic. In the presence of light-tailed random .delays, we show that the throughput decreases according to the inverse of the logarithm of the number of receivers. We find analytically an upper and a lower bound for the throughput degradation. Within these bounds, we characterize the degradation, which is obtained for various tree topologies. In particular, we observe that a class of trees commonly found in IP multicast sessions is significantly more sensitive to traffic variability than other topologies