As the distribution of the video over the Internet becomes main- stream and its consumption moves from the computer to the TV screen, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand if and how video quality affects user engagement and how to best invest their resources to optimize video quality. This paper is a first step towards addressing these questions. We use a unique dataset that spans different content types, including short video on demand (VoD), long VoD, and live content from popular video con- tent providers. Using client-side instrumentation, we measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events.

Internet video delivery has been motivating research in multicast routing, quality of service (QoS), and the service model of the Internet itself for the last 15 years. Multicast delivery has the potential to deliver a large amount of content that currently cannot be delivered through broadcast. IP and overlay multicast are two architectures proposed to provide multicast support. A large body of research has been done with IP multicast and QoS mechanisms for IP multicast since the late 1980s. In the past five years, overlay multicast research has gained momentum with a vision to accomplish ubiquitous multicast delivery that is efficient and scales in the dimensions of the number of groups, number of receivers, and number of senders. This work presents an overview of the issues facing both IP and overlay multicast and the approaches that researchers are taking to solve them. Many of these approaches take advantage of a rich interface, beyond a single rate video stream, between the coding and delivery mechanisms. The semantics of this interface is an important question for future research and we discuss this with insight from experience on delivery technologies.

A large number of overlay multicast protocols have been developed, almost all of which assume universal connectivity between end hosts. However, in reality, this assumption is not valid with widespread use of Network Address Translators (NAT) and firewalls. The impact of NAT and firewall connectivity restrictions on overlay multicast, es-pecially in the application-endpoint setting, has not been seriously considered. In this paper, we argue that it is critical to consider con-nectivity restrictions because NAT and firewall hosts make up a large fraction of the endpoints, affecting proper functionality as well as performance of overlay multicast protocols. We present several de-sign enhancements that explicitly consider connectivity restrictions in overlay multicast and evaluate the design space and tradeoffs based on real Internet broadcasts and Internet testbed experiments.

While application end-point architectures have proven to be viable solutions for large-scale distributed applications such as distributed computing and file-sharing, there is little known about its feasibility for more bandwidth-demanding applications such as live streaming. Heterogeneity in bandwidth resources and dynamic group membership, inherent properties of application end-points, may adversely affect the construction of a usable and efficient overlay. At large scales, the problems become even more challenging. In this paper, we study one of the most prominent architectural issues in overlay multicast: the feasibility of supporting large-scale groups using an application end-point architecture. We look at three key requirements for feasibility: (i) are there enough resources to construct an overlay, (ii) can a stable and connected overlay be maintained in the presence of group dynamics, and (iii) can an efficient overlay be constructed? Using traces from a large content delivery network, we characterize the behavior of users watching live audio and video streams. We show that in many common real-world scenarios, all three requirements are satisfied. In addition, we evaluate the performance of several design alternatives and show that simple algorithms have the potential to meet these requirements in practice. Overall, our results argue for the feasibility of supporting large-scale live streaming using an application end-point architecture.