Capacity of P2P on-demand streaming with simple, robust and decentralized control

The performance of large-scaled peer-to-peer (P2P) video-on-demand (VoD) streaming systems can be very challenging to analyze. In practical P2P VoD systems, each peer only interacts with a small number of other peers/neighbors. Further, its upload capacity may vary randomly, and both its downloading position and content availability change dynamically. In this paper, we rigorously study the achievable streaming capacity of large-scale P2P VoD systems with sparse connectivity among peers, and investigate simple and decentralized P2P control strategies that can provably achieve close-to-optimal streaming capacity. We first focus on a single streaming channel. We show that a close-to-optimal streaming rate can be asymptotically achieved for all peers with high probability as the number of peers N increases, by assigning each peer a random set of Θ(log N) neighbors and using a uniform rate-allocation algorithm. Further, the tracker does not need to obtain detailed knowledge of which chunks each peer caches, and hence incurs low overhead. We then study multiple streaming channels where peers watching one channel may help in another channel with insufficient upload bandwidth. We propose a simple random cache-placement strategy, and show that a close-to-optimal streaming capacity region for all channels can be attained with high probability, again with only Θ(logN) per-peer neighbors. These results provide important insights into the dynamics of large-scale P2P VoD systems, which will be useful for guiding the design of improved P2P control protocols. © 2013 IEEE.published_or_final_versio

Capacity of P2P On-Demand Streaming With Simple, Robust, and Decentralized Control

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Capacity of p2p on-demand streaming with simple, robust and decentralized control

Abstract-The performance of large-scaled peer-to-peer (P2P) video-on-demand (VoD) streaming systems can be very challenging to analyze. In practical P2P VoD systems, each peer only interacts with a small number of other peers/neighbors. Further, its upload capacity may vary randomly, and both its downloading position and content availability change dynamically. In this paper, we rigorously study the achievable streaming capacity of large-scale P2P VoD systems with sparse connectivity among peers, and investigate simple and decentralized P2P control strategies that can provably achieve close-to-optimal streaming capacity. We first focus on a single streaming channel. We show that a closeto-optimal streaming rate can be asymptotically achieved for all peers with high probability as the number of peers N increases, by assigning each peer a random set of Θ(log N ) neighbors and using a uniform rate-allocation algorithm. Further, the tracker does not need to obtain detailed knowledge of which chunks each peer caches, and hence incurs low overhead. We then study multiple streaming channels where peers watching one channel may help in another channel with insufficient upload bandwidth. We propose a simple random cache-placement strategy, and show that a close-to-optimal streaming capacity region for all channels can be attained with high probability, again with only Θ(log N ) per-peer neighbors. These results provide important insights into the dynamics of large-scale P2P VoD systems, which will be useful for guiding the design of improved P2P control protocols

The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results

vSkyConf: Cloud-assisted Multi-party Mobile Video Conferencing

As an important application in the busy world today, mobile video conferencing facilitates virtual face-to-face communication with friends, families and colleagues, via their mobile devices on the move. However, how to provision high-quality, multi-party video conferencing experiences over mobile devices is still an open challenge. The fundamental reason behind is the lack of computation and communication capacities on the mobile devices, to scale to large conferencing sessions. In this paper, we present vSkyConf, a cloud-assisted mobile video conferencing system to fundamentally improve the quality and scale of multi-party mobile video conferencing. By novelly employing a surrogate virtual machine in the cloud for each mobile user, we allow fully scalable communication among the conference participants via their surrogates, rather than directly. The surrogates exchange conferencing streams among each other, transcode the streams to the most appropriate bit rates, and buffer the streams for the most efficient delivery to the mobile recipients. A fully decentralized, optimal algorithm is designed to decide the best paths of streams and the most suitable surrogates for video transcoding along the paths, such that the limited bandwidth is fully utilized to deliver streams of the highest possible quality to the mobile recipients. We also carefully tailor a buffering mechanism on each surrogate to cooperate with optimal stream distribution. We have implemented vSkyConf based on Amazon EC2 and verified the excellent performance of our design, as compared to the widely adopted unicast solutions.Comment: 10 page