Business model with discount incentive in a P2P-cloud multimedia streaming system

Today P2P faces two important challenges: design of mechanisms to encourage users' collaboration in multimedia live streaming services; design of reliable algorithms with QoS provision, to encourage the multimedia providers employ the P2P topology in commercial live streaming systems. We believe that these two challenges are tightly-related and there is much to be done with respect. This paper analyzes the effect of user behavior in a multi-tree P2P overlay and describes a business model based on monetary discount as incentive in a P2P-Cloud multimedia streaming system. We believe a discount model can boost up users' cooperation and loyalty and enhance the overall system integrity and performance. Moreover the model bounds the constraints for a provider's revenue and cost if the P2P system is leveraged on a cloud infrastructure. Our case study shows that a streaming system provider can establish or adapt his business model by applying the described bounds to achieve a good discount-revenue trade-off and promote the system to the users

Decision Strategies for a P2P Computing System

Peer-to-Peer (P2P) computing (also called ‘public-resource computing’) is an effective approach to perform computation of large tasks. Currently used P2P computing systems (e.g., BOINC) are most often centrally managed, i.e., the final result of computations is created at a central node using partial results – what may be not efficient in the case when numerous participants are willing to download the final result. In this paper, we propose a novel approach to P2P computing systems. We assume that results can be delivered to all peers in a distributed way using three types of network flows: unicast, Peer-to-Peer and anycast. We describe our concept of the system architecture with a special focus on the decision strategies developed for system participants. Using our discrete realtime simulator we evaluate the proposed strategies in various scenarios and present a comprehensive analysis of obtained results. According to obtained results, the Peer-to-Peer flow provides lower operational cost of the computing system compared to unicast and anycast flows. Moreover, an appropriate selection of decision strategy can significantly reduce the operational cost

Video-on-Demand over Internet: a survey of existing systems and solutions

Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client/server architecture experiences scalability issues to provide video streaming services, so there have been many proposals of systems, mostly based on a peer-to-peer or on a hybrid server/peer-to-peer solution, to solve this issue. This work presents a survey of the currently existing or proposed systems and solutions, based upon a subset of representative systems, and defines selection criteria allowing to classify these systems. These criteria are based on common questions such as, for example, is it video-on-demand or live streaming, is the architecture based on content delivery network, peer-to-peer or both, is the delivery overlay tree-based or mesh-based, is the system push-based or pull-based, single-stream or multi-streams, does it use data coding, and how do the clients choose their peers. Representative systems are briefly described to give a summarized overview of the proposed solutions, and four ones are analyzed in details. Finally, it is attempted to evaluate the most promising solutions for future experiments. Résumé La vidéo à la demande est un service où des films sont fournis à distance aux utilisateurs avec u

Mathematical analysis of scheduling policies in peer-to-peer video streaming networks

Las redes de pares son comunidades virtuales autogestionadas, desarrolladas en la capa de aplicación sobre la infraestructura de Internet, donde los usuarios (denominados pares) comparten recursos (ancho de banda, memoria, procesamiento) para alcanzar un fin común. La distribución de video representa la aplicación más desafiante, dadas las limitaciones de ancho de banda. Existen básicamente tres servicios de video. El más simple es la descarga, donde un conjunto de servidores posee el contenido original, y los usuarios deben descargar completamente este contenido previo a su reproducción. Un segundo servicio se denomina video bajo demanda, donde los pares se unen a una red virtual siempre que inicien una solicitud de un contenido de video, e inician una descarga progresiva en línea. El último servicio es video en vivo, donde el contenido de video es generado, distribuido y visualizado simultáneamente. En esta tesis se estudian aspectos de diseño para la distribución de video en vivo y bajo demanda. Se presenta un análisis matemático de estabilidad y capacidad de arquitecturas de distribución bajo demanda híbridas, asistidas por pares. Los pares inician descargas concurrentes de múltiples contenidos, y se desconectan cuando lo desean. Se predice la evolución esperada del sistema asumiendo proceso Poisson de arribos y egresos exponenciales, mediante un modelo determinístico de fluidos. Un sub-modelo de descargas secuenciales (no simultáneas) es globalmente y estructuralmente estable, independientemente de los parámetros de la red. Mediante la Ley de Little se determina el tiempo medio de residencia de usuarios en un sistema bajo demanda secuencial estacionario. Se demuestra teóricamente que la filosofía híbrida de cooperación entre pares siempre desempeña mejor que la tecnología pura basada en cliente-servidor

Estimating Self-Sustainability in Peer-to-Peer Swarming Systems

Peer-to-peer swarming is one of the \emph{de facto} solutions for distributed content dissemination in today's Internet. By leveraging resources provided by clients, swarming systems reduce the load on and costs to publishers. However, there is a limit to how much cost savings can be gained from swarming; for example, for unpopular content peers will always depend on the publisher in order to complete their downloads. In this paper, we investigate this dependence. For this purpose, we propose a new metric, namely \emph{swarm self-sustainability}. A swarm is referred to as self-sustaining if all its blocks are collectively held by peers; the self-sustainability of a swarm is the fraction of time in which the swarm is self-sustaining. We pose the following question: how does the self-sustainability of a swarm vary as a function of content popularity, the service capacity of the users, and the size of the file? We present a model to answer the posed question. We then propose efficient solution methods to compute self-sustainability. The accuracy of our estimates is validated against simulation. Finally, we also provide closed-form expressions for the fraction of time that a given number of blocks is collectively held by peers.Comment: 27 pages, 5 figure

Collusion in Peer-to-Peer Systems

Peer-to-peer systems have reached a widespread use, ranging from academic and industrial applications to home entertainment. The key advantage of this paradigm lies in its scalability and flexibility, consequences of the participants sharing their resources for the common welfare. Security in such systems is a desirable goal. For example, when mission-critical operations or bank transactions are involved, their effectiveness strongly depends on the perception that users have about the system dependability and trustworthiness. A major threat to the security of these systems is the phenomenon of collusion. Peers can be selfish colluders, when they try to fool the system to gain unfair advantages over other peers, or malicious, when their purpose is to subvert the system or disturb other users. The problem, however, has received so far only a marginal attention by the research community. While several solutions exist to counter attacks in peer-to-peer systems, very few of them are meant to directly counter colluders and their attacks. Reputation, micro-payments, and concepts of game theory are currently used as the main means to obtain fairness in the usage of the resources. Our goal is to provide an overview of the topic by examining the key issues involved. We measure the relevance of the problem in the current literature and the effectiveness of existing philosophies against it, to suggest fruitful directions in the further development of the field

Clustering and Sharing Incentives in BitTorrent Systems

Peer-to-peer protocols play an increasingly instrumental role in Internet content distribution. Consequently, it is important to gain a full understanding of how these protocols behave in practice and how their parameters impact overall performance. We present the first experimental investigation of the peer selection strategy of the popular BitTorrent protocol in an instrumented private torrent. By observing the decisions of more than 40 nodes, we validate three BitTorrent properties that, though widely believed to hold, have not been demonstrated experimentally. These include the clustering of similar-bandwidth peers, the effectiveness of BitTorrent's sharing incentives, and the peers' high average upload utilization. In addition, our results show that BitTorrent's new choking algorithm in seed state provides uniform service to all peers, and that an underprovisioned initial seed leads to the absence of peer clustering and less effective sharing incentives. Based on our observations, we provide guidelines for seed provisioning by content providers, and discuss a tracker protocol extension that addresses an identified limitation of the protocol