Group communication primitives have broad utility as building blocks for distributed applications. The challenge is to create and maintain the distributed structures that support these primitives while accounting for volatile end-nodes and variable network characteristics. Most solutions proposed to date rely on complex algorithms or global information, thus limiting the scale of deployments and acceptance outside the academic realm.

This article introduces a low-complexity, self-organizing solution for maintaining multicast trees, that we refer to as UMM (Unstructured Multisource Multicast). UMM uses traditional distributed systems techniques: layering, soft-state, and passive data collection to adapt to the dynamics of the physical network and maintain data dissemination trees. The result is a simple, adaptive system with lower overheads than more complex alternatives. We have implemented UMM and evaluated it on up to 1024-node emulated ModelNet networks and on the PlanetLab testbed.. Extensive experimental evaluations and quantitative comparisons with alternative solutions demonstrate UMM?s low overhead, efficient network usage, and ability to quickly adapt to network changes and to recover from failures.