On-Demand Media Streaming over the Internet

2012 IV International Congress on Ultra Modern Telecommunications and Control Systems, 2012

We propose a mathematical framework for the optimal design of a video on-demand (VoD) application under regime. Peers join the network following a poissonian process, download progressively one or possibly many concurrent video contents, and abort the system when they wish. The system is supported by static servers managed by the operator, called super-peers, and the altruism of peers, that upload resources and might stay online even after completing downloading. Our goal is to minimize the expected download time perceived by end-users under regime. We propose a general fluid model, and show that it is stable, reaching its regime. Via the Little's law, we find closed expressions for the expected waiting time under regime in terms of the popularity of different contents, file sharing efficiency and other network parameters. We state theoretically that this system outperforms traditional Content Delivery Networks (CDN). The operator can decide only the number of video replicas stored in each super-peer, a fact that has a direct impact on the mean waiting times. Hence, a combinatorial optimization problem is introduced, whose nature is similar to the multi-knapsack problem (i.e. the items are video contents, and the knapsacks are the super-peers storage). A greedy randomized resolution is here designed, and a comparison between traditional content distribution systems promotes the deployment of peer-to-peer video on-demand services. Finally, real-life scenarios are studied based on traces taken from YouTube. The results confirm that the peer-to-peer model can outperform five times the throughput of traditional CDN under flash-crowded scenarios.

2002

We study the economic aspects of P2P systems. We present a cost-profit analysis of a media streaming service deployed over a peer-to-peer (P2P) infrastructure. We consider the limited capacity as well as the heterogeneity of peers in the analysis. The analysis shows that with the appropriate incentives for participating peers, the service provider achieves more profit. In addition, the analysis shows how the service provider can maximize its revenue by controlling the amount of incentives offered to peers.

Networks for Grid Applications, 2009

Most of the work on grid technology in the video area has been generally restricted to aspects of resource scheduling and replica management. The traffic of such a service has a lot of characteristics in common with that of the traditional video service. However the architecture and user behavior in grid networks are quite different from those of the traditional Internet. Considering the potential of grid networks and video sharing services, measuring and analyzing P2P IPTV traffic are important and fundamental works in the field of grid networks.

IEEE Transactions on Parallel and Distributed Systems, 2000

We analyze a peer-assisted Video-on-Demand (VoD) system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled nonsequential swarms. Our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, and nonstationary traffic conditions, which have not been documented or analyzed before. Finally, we provide important hints for the design of efficient peer-assisted VoD systems under server capacity constraints.

Packet Video 2007, 2007

Performance analysis frameworks for P2P networks are in great demand by Internet Service Providers (ISP) and telecommunications companies in order to redesign their systems so as to support the new paradigm. The target of this paper is to propose an analytical model of a real-time video transmission system using P2P to achieve multipoint communication on the current Internet. The system considered is defined in such a way as to maximize the number of users, while guaranteeing a given quality of service level in terms of the maximum number of hops connecting them with the video source.

Multimedia Systems, 2009

This paper studies the conditions under which peer-to-peer (P2P) technology may be beneficial in providing IPTV services over typical network architectures. It has three major contributions. First, we contrast two network models used to study the performance of such a system: a commonly used logical "Internet as a cloud" model and a "physical" model that reflects the characteristics of the underlying network. Specifically, we show that the cloud model overlooks important architectural aspects of the network and may drastically overstate the benefits of P2P technology by a factor of 3 or more. Second, we propose an algorithm called Zebra that pre-stripes content across multiple peers during idle hours to speed up P2P content delivery in an IPTV environment with limited upload bandwidth. We also perform simulations to measure Zebra's effectiveness at reducing load on the content server during peek hours. Third, we provide a cost-benefit analysis of P2P video content delivery, focusing on the profit trade-offs for different pricing/incentive models rather than purely on capacity maximization. In particular, we find that under high volume of video demand, a P2P built-in incentive model performs better than any other model, while the conventional no-P2P model generates more profits when the request rate is low. The flat-reward model generally falls in between the usage-based model and the built-in model in terms of profitability except for low request rates. We also find that built-in and flat-reward models are more profitable than the usagebased model for a wide range of subscriber community sizes.

2004

In this paper we study the 'service capacity' of peer to peer (P2P) file sharing applications. We begin by considering a transient regime which is key to capturing the ability of such systems to handle bursty traffic, e.g., flash crowds. In this context our models, based on age dependent branching processes, exhibit exponential growth in service capacity, and permit the study of sensitivity of this growth to system policies and parameters. Then we consider a model for such systems in steady state and show how the average delay seen by peers would scale in the offered load and rate at which peers exit the system. We find that the average delays scale well in the offered load. In particular the delays are upper bounded by some constant given any offered load and even decrease in the offered load if peers exit the system slowly. We validate many of our findings by analyzing traces obtained from a second generation P2P application called BitTorrent. Index Terms-system design, network measurements, peer to peer applications, flash crowds, service capacity, performance evaluation, mathematical modeling 0-7803-8356-7

2003

In this paper we consider the sensitivity of the 'service capacity' of peer to peer (P2P) file sharing applications to demands, user cooperation, and providing incentives for cooperation through fairness guarantees. To do so we propose models for both the steady state performance and the transient characteristics of the system. Both are of interest since, from the perspective of a given file, demands are prone to be initially bursty, e.g., flash crowds, and subsequently be roughly 'stationary.' We will show that P2P systems can be exceptionally responsive to bursty demands by increasing their service capacity exponentially, while exhibiting nice performance scaling to the offered loads during stationary regimes. We also study system characteristics associated with various fairness criteria. We provide partial validation of our models and conclusions based on traces obtained from a second generation P2P application.

2012

We analyze a peer-assisted Video-on-Demand system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled Bit-Torrent like swarms. Our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, nonstationary traffic conditions, which have not been documented or analyzed before. We provide an analytical methodology to design efficient peer-assisted VoD systems and optimal resource allocation strategies under server capacity constraints.