Live peer to peer (P2P) media streaming faces many challenges such as peer unreliability and bandwidth heterogeneity. To effectively address these challenges, general "mesh" based P2P streaming architectures have recently been adopted. Mesh-based systems allow peers to aggregate bandwidth from multiple neighbors, and dynamically adapt to changing network conditions and neighbor failures. However, a drawback of mesh-based overlays is that it is difficult to guarantee network connectivity in a distributed fashion, especially when network locality needs to be optimized. This paper introduces a new P2P streaming framework called DagStream, which (1) organizes peers into a directed acyclic graph (DAG) where each node maintains at least k parents, thus has provable network connectivity (and hence failure resilience), and (2) enables peers to quickly achieve locality awareness in a distributed fashion, thus ensures efficient network resource usage. Our experiment results in both simulation and wide area environment show that with our DagStream protocol, peers can quickly self-organize into a locality aware DAG. Further, by selecting additional parents as needed, peers can achieve good streaming quality commensurate with their downlink bandwidth.
By composing distributed, autonomous services dynamically to provide new functionalities, service composition provides an attractive way for customized multimedia content production and delivery. Previous
research work has addressed various aspects of service composition such as composibility, QoS-awareness, and load balancing. However, most of the work has focused on applications where data flow from a single source is processed by intermediate services and
then delivered to a single destination. In this paper, we address the service composition problem for advanced multimedia applications where data flows from multiple content sources are processed and aggregated into a composite flow, which is then delivered to one or more destinations, possibly after being customized for each receiver. We formally define the problem and prove its NP hardness. We also design a heuristic algorithm to solve the problem. Our algorithm has the following attractive features: (1) it is effective at finding low cost composition solutions; (2) it has the ability to trade off computation overhead for better results; (3) it is
efficient and can scale to relatively large number of network nodes and component services.