Although IP Multicast is an effective network primitive for best-effort, large-scale, multi-point communication, many multicast applications such as shared whiteboards, multi-player games and software distribution require reliable data delivery. Building services like reliable sequenced delivery on top of IP Multicast has proven to be a hard problem. The enormous extent of network and end-system heterogeneity in multipoint communication exacerbates the design of scalable end-to-end reliable multicast protocols. In this paper, we propose a radical departure from the traditional end-to-end model for reliable multicast and instead propose a hybrid approach that leverages the successes of unicast reliability protocols such as TCP while retaining the efficiency of IP multicast for multi-point data delivery. Our approach splits a large heterogeneous reliable multicast session into a number of multicast data groups of co-located homogeneous participants. A collection of application-aware agents--Reliable Multicast proxies (RMXs)--organizes these data groups into a spanning tree using an overlay network of TCP connections. Sources transmit data to their local group, and the RNLX in that group forwards the data towards the rest of the data groups. RMXs use detailed knowledge of application semantics to adapt to the effects of heterogeneity in the environment. To demonstrate the efficacy of our architecture, we have built a prototype implementation that can be customized for different kinds of applications.

The IP Multicast service model extends the traditional best effort Internet datagram delivery service for efficient multi-point packet delivery. However, in spite of a decade of research on multicast protocols and applications, a globally deployed multicast service is nowhere in sight, hindered by multitudes of problems such as manageability, lack of a robust inter-domain multicast routing protocol, scalability, and heterogeneity. In this work, we propose a new model for Internet multicast where we view multi-point delivery not as a network primitive but rather as an application-level infrastructure service. Our architecture relies on a collection of strategically placed network agents that collaboratively provides the multicast service for a session. Clients locate a nearby agent and tap into the session via that agent. Agents organize themselves into an overlay network of unicast connections and build data distribution trees on top of this overlay structure. This model effectively pa...

Scalability is of paramount importance in the design of reliable multicast transport protocols, and requires a careful consideration of a number of problems such as feedback implosion, retransmission scoping, distributed loss recovery, and congestion control. In this paper, we present a reliable multicast architecture that invokes active services at strategic locations inside the network to comprehensively address these challenges. Active services provide the ability to quickly and efficiently recover from loss at the point of loss. They also exploit the physical hierarchy for feedback aggregation and effective retransmission scoping with minimal router support. We present two protocols, one for packet loss recovery and another for congestion control, and describe an experimental testbed where these have been implemented. Analysis, simulation, and experimental results are used to demonstrate that our active services architecture improves resource usage, reduces latency for loss recover...

IP Multicast has proven to be an effective communication primitive for best effort, large-scale, multi-point audio/video conferencing applications. While the best-effort transport of real-time digital audio/video is a relatively straightforward and well understood problem, many other applications like multicast-based shared whiteboards and shared text editors are more challenging to design because their underlying media require reliable transport, i.e., a "reliable multicast" protocol. The design of scalable end-to-end reliable multicast protocols has unfortunately proven to be an especially hard problem, exacerbated by the enormous degree of network and system heterogeneity present in the Internet. In this work, we propose to tackle the heterogeneity problem with a hybrid model for reliable multicast that relies in part on end-to-end loss recovery mechanisms and in part on intelligent and application-aware adaptation carried out within the network. In our framework, a network of applicat...