Scalable and topologically-aware application-layer multicast

We present a scalable and topologically-aware application-layer multicast approach, specially designed for large-scale distributed applications. The proposed approach constructs topologically-aware data paths which are based on topological clustering of multicast group members. The approach does not require any exact network topology information, but instead requires the relative location information of members using landmarks. We partition the members into topologically-aware clusters based on the ordering of their close landmarks. We hierarchically arrange the clusters and separate data paths into two types (i.e., inside-cluster path and outside-cluster path) to exclude outsider nodes, not belonging to the same cluster, from the inside-cluster paths. Our results on performance evaluation show that constructing topologically-aware data paths can reduce unnecessary high latency and redundant network resource usage with low overhead over existing scalable approaches.