In order to assess service quality of a networked application (such as a streaming session), distributed monitoring servers need to continuously collect application-specific performance metrics in real time. Much of the previous work to address this is to use distributed aggregation tree (DAT) rooted at each monitor. However, this approach often leads to high monitoring delay and network stress. In this paper, we study a highly scalable monitoring network for distributed applications. In the network, there are distributed monitors collecting application performance in two steps: first, client applications report their performance to some proxies by means of a client overlay, and then the proxies report the performance to the distributed monitors using another proxy overlay. We first formulate the problem to construct overlays minimizing monitoring delay. The problem is shown to be NP-hard. Then, we present a simple, efficient, and scalable monitoring algorithm called SMon, which continuously reduces network diameter in real time in a distributed manner. Through simulations and actual experimental measurements with implementation, we show that SMon achieves low monitoring delay, network stress, and protocol overhead for distributed applications.

Although peer-to-peer (P2P) streaming can efficiently deliver live video content to large user populations, existing applications often suffer from limited video quality, periodic hiccups, and high delays. To overcome some of the limitations of today's unstructured (mesh-based) designs, we have developed and deployed FastMesh-SIM, a novel P2P streaming system that leverages proxies, push-mechanism and IP multicast to achieve lower playback delay and better stream continuity. Having control over a real P2P streaming system also gives us a rare opportunity to conduct controlled experiments where we vary major design parameters (e.g., push vs. pull delivery, IP multicast support, streaming rate, and video segment size) under a range of operating conditions (e.g., dynamics of peer churn, and different network configurations), while collecting detailed, fine-granular measurements (e.g., the various components of end-to-end delay). Analysis of the measurement data, consisting of seven trials of streaming several live TV channels for more than 100 hours to 140 peers, sheds light on how design decisions and the operating environment affect important performance metrics. Our experiments show that a push-based, proxy-P2P system can achieve low delay and good video quality, though network bottlenecks on long-haul connections can sometimes cause disruptions in a global deployment. Theory-practice gaps observed from the data are also discussed. Large-scale, global experiments are now being carried out.