Providing video-on-demand using peer-to-peer networks

Digital media companies have recently started embracing peer-assisted distribution networks as an alternative to traditional client-server architectures [5]. Such Peer-to-Peer (P2P) architectures ensure a fast and scalable delivery of media content. However, their drawback is that users need to often wait for the full video to be downloaded before they can start watching it. While a lot of effort has gone into optimizing the distribution of large video files using P2P swarming techniques, little research has been done on how to ensure a small start-up time and a sustainable playback rate to enable a play-asyou-download experience. In this work, we address the challenges underlying the problem of near Video-on-Demand (nVoD) using P2P swarming systems, and provide evidence that high-quality nVoD is feasible. In particular, we investigate the scheduling problem of efficiently disseminating the blocks of a video file in a P2P mesh-based system, and show that pre-fetching and network coding techniques can provide significant benefits. Our results show that, for videos which are 120 minutes in duration, 10 minutes ( ≈ 8 % of the video’s length) of buffering at start-up can enable playback rates that are close (up to 80 − 90%) to the access link capacity, even under dynamic changes of the user population. 1

Is high-quality vod feasible using p2p swarming

Peer-to-peer technologies are increasingly becoming the medium of choice for delivering media content, both professional and homegrown, to large user populations. Indeed, current P2P swarming systems have been shown to be very efficient for large-scale content distribution with few server resources. However, such systems have been designed for generic file distribution and provide a limited user experience for viewing media content. For example, users need to wait to download the full video before they can start watching it. In general, the main challenge resides in designing systems that ensure that users can start watching a movie at any point in time, with small start-up times and sustainable playback rates. In this work, we address the issues of providing a Video-on-Demand (VoD) using P2P mesh-based networks. We show that providing high quality VoD using P2P is feasible using a combination of techniques including (a) network coding, (b) optimized resource allocation across different parts of the video, and (c) overlay topology management algorithms. Our evaluation also shows that systems that do not optimize in all these dimensions could significantly under-utilize the network resources resulting in poor VoD performance. We present our results based on simulations and a prototype implementation. Categories and Subject Descriptor

Abstract Shark: Scaling File Servers via Cooperative Caching

Network file systems offer a powerful, transparent interface for accessing remote data. Unfortunately, in current network file systems like NFS, clients fetch data from a central file server, inherently limiting the system’s ability to scale to many clients. While recent distributed (peer-topeer) systems have managed to eliminate this scalability bottleneck, they are often exceedingly complex and provide non-standard models for administration and accountability. We present Shark, a novel system that retains the best of both worlds—the scalability of distributed systems with the simplicity of central servers. Shark is a distributed file system designed for largescale, wide-area deployment, while also providing a dropin replacement for local-area file systems. Shark introduces a novel cooperative-caching mechanism, in which mutually-distrustful clients can exploit each others ’ file caches to reduce load on an origin file server. Using a distributed index, Shark clients find nearby copies of data, even when files originate from different servers. Performance results show that Shark can greatly reduce server load and improve client latency for read-heavy workloads both in the wide and local areas, while still remaining competitive for single clients in the local area. Thus, Shark enables modestly-provisioned file servers to scale to hundreds of read-mostly clients while retaining traditional usability, consistency, security, and accountability.

Abstract Shark: Scaling File Servers via Cooperative Caching

Network file systems offer a powerful, transparent interface for accessing remote data. Unfortunately, in current network file systems like NFS, clients fetch data from a central file server, inherently limiting the system’s ability to scale to many clients. While recent distributed (peer-topeer) systems have managed to eliminate this scalability bottleneck, they are often exceedingly complex and provide non-standard models for administration and accountability. We present Shark, a novel system that retains the best of both worlds—the scalability of distributed systems with the simplicity of central servers. Shark is a distributed file system designed for largescale, wide-area deployment, while also providing a dropin replacement for local-area file systems. Shark introduces a novel cooperative-caching mechanism, in which mutually-distrustful clients can exploit each others ’ file caches to reduce load on an origin file server. Using a distributed index, Shark clients find nearby copies of data, even when files originate from different servers. Performance results show that Shark can greatly reduce server load and improve client latency for read-heavy workloads both in the wide and local areas, while still remaining competitive for single clients in the local area. Thus, Shark enables modestly-provisioned file servers to scale to hundreds of read-mostly clients while retaining traditional usability, consistency, security, and accountability.

Algorithms, Experimentation

Peer-to-peer technologies are increasingly becoming the medium of choice for delivering media content, both professional and homegrown, to large user populations. Indeed, current P2P swarming systems have been shown to be very efficient for large-scale content distribution with few server resources. However, such systems have been designed for generic file distribution and provide a limited user experience for viewing media content. For example, users need to wait to download the full video before they can start watching it. In general, the main challenge resides in designing systems that ensure that users can start watching a movie at any point in time, with small start-up times and sustainable playback rates. In this work, we address the issues of providing a Video-on-Demand (VoD) using P2P mesh-based networks. We show that providing high quality VoD using P2P is feasible using a combination of techniques including (a) network coding, (b) optimized resource allocation across different parts of the video, and (c) overlay topology management algorithms. Our evaluation also shows that systems that do not optimize in all these dimensions could significantly under-utilize the network resources resulting in poor VoD performance. We present our results based on simulations and a prototype implementation. Categories and Subject Descriptor

Democratizing Content Distribution

"Behold how good and how pleasant it is for brethren to dwell together in unity."-- Psalms 133-1 To my future wife Jennifer for her warmth and support and To my brother Daniel for his courage of convictions