Traditionally, Internet Service Providers (ISPs) make profit by providing Internet connectivity, while content providers (CPs) play the more lucrative role of delivering content to users. As network connectivity is increasingly a commodity, ISPs have a strong incentive to offer content to their subscribers by deploying their own content distribution infrastructure. Providing content services in an ISP network presents new opportunities for coordination between traffic engineering (to select efficient routes for the traffic) and server selection (to match servers with subscribers). In this work, we develop a mathematical framework that considers three models with an increasing amount of cooperation between the ISP and the CP. We show that separating server selection and traffic engineering leads to sub-optimal equilibria, even when the CP is given accurate and timely information about the ISP's network in a partial cooperation. More surprisingly, extra visibility may result in a less efficient outcome and such performance degradation can be unbounded. Leveraging ideas from cooperative game theory, we propose an architecture based on the concept of Nash bargaining solution. Simulations on realistic backbone topologies are performed to quantify the performance differences among the three models. Our results apply both when a network provider attempts to provide content, and when separate ISP and CP entities wish to cooperate. This study is a step toward a systematic understanding of the interactions between those who provide and operate networks and those who generate and distribute content.

Peer-assisted streaming is a promising way for service providers to offer high-quality IPTV to consumers at reasonable cost. In peerassisted streaming, the peers exchange video chunks with one another, and receive additional data from the central server as needed.In this paper, we analyze how to provision resources for the streaming system, in terms of the server capacity, the video quality, and the depth of the distribution trees that deliver the content. We derive the performance bounds for minimum server load, maximum streaming rate, and minimum tree depth under different peer selection constraints. Furthermore, we show that our performance bounds are actually tight, by presenting algorithms for constructing trees that achieve our bounds.