Scalable Reliable Multicast with Layered Recovery and Low-Overhead Network Delay Estimation

We study two problems that arise in designing scalable reliable multicast protocols. The first problem we study is that of localizing repair packets when packets are lost. When repair packets are multicasted, a highly lossy receiver may swamp the entire multicast ``group'''' with duplicate repair packets thereby wasting bandwidth; thus, the protocols need repair locality. In this paper, we present a novel multicast layering protocol where the sender proactively distributes FEC repair packets among multiple multicast groups. Receivers can selectively tune in to a subset of these multicast groups to obtain only the number of repair packets they require. We present a highly efficient algorithm that dynamically determines the optimal distribution of FEC repair packets to a given (small constant) number of multicast groups. The running time of this algorithm is independent of the number of receivers in the multicast session, and it is hence scalable. The second problem we address is to estimate the network delay between each pair of nodes in the multicast session. This key parameter is useful, among other things, in suppressing the implosion of request and repair packets, and in detecting congestion. Existing implementations use $O(n)$ multicasts with $O(n)$ message size each (total of $O(n^2)$ bits); here, $n$ is the session size. This paper presents a new delay estimation protocol that requires $O(n)$ multicasts only with $O(1)$ message size each. This protocol is hence more scalable. Furthermore, it does not require synchronized clocks, or any knowledge of network topology or the session size. Our solutions to these two problems can be integrated into many known reliable multicast protocols to enhance their scalability. For concreteness, we focus on singly scoped and hierarchically scoped SRM as well as tree-based protocols and present combined protocols incorporating our solutions into each of them. Our simulation experiments suggest that our solutions can substantially enhance the scalability of these reliable multicast protocols.

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