BitTorrent under a microscope : towards static QoS provision in dynamic peer-to-peer networks

For peer-to-peer (P2P) networks continually to flourish, QoS provision is critical. However, the P2P networks are notoriously dynamic and heterogeneous. As a result, QoS provision in P2P networks is a challenging task with nodes of the varying and intermittent throughput. This raises a fundamental problem: is stable and delicate QoS provision achievable in the highly dynamic and heterogeneous P2P networks? In this work, we investigate BitTorrent (BT) with the particular interest in its QoS performance in the highly dynamic and heterogeneous network. Our contributions are two-fold. First, we develop an analytical model to examine a randomly selected BT node under a microscope. Based on the model, we study the mean and variance of nodal download rate in the dynamic network and the performance of BT in QoS provision under different levels of peer churns. Our analysis unveils that although BT strives to provide nodes with guaranteed throughput, due to the network dynamics, the download rates of the peers oscillate extraordinarily and can hardly converge to the target QoS as proposed in previous literature. Second, to improve the QoS provision, we propose an enhanced protocol incorporating with BT. The proposed protocol enables nodes to quickly and elaborately search their uploaders, and as a result, achieve guaranteed and stable QoS in the dynamic networks. Using both analysis and simulations, we validate the effectiveness of the proposed protocol in comparisons with the original BT

Systems-compatible Incentives

Originally, the Internet was a technological playground, a collaborative endeavor among researchers who shared the common goal of achieving communication. Self-interest used not to be a concern, but the motivations of the Internet's participants have broadened. Today, the Internet consists of millions of commercial entities and nearly 2 billion users, who often have conflicting goals. For example, while Facebook gives users the illusion of access control, users do not have the ability to control how the personal data they upload is shared or sold by Facebook. Even in BitTorrent, where all users seemingly have the same motivation of downloading a file as quickly as possible, users can subvert the protocol to download more quickly without giving their fair share. These examples demonstrate that protocols that are merely technologically proficient are not enough. Successful networked systems must account for potentially competing interests. In this dissertation, I demonstrate how to build systems that give users incentives to follow the systems' protocols. To achieve incentive-compatible systems, I apply mechanisms from game theory and auction theory to protocol design. This approach has been considered in prior literature, but unfortunately has resulted in few real, deployed systems with incentives to cooperate. I identify the primary challenge in applying mechanism design and game theory to large-scale systems: the goals and assumptions of economic mechanisms often do not match those of networked systems. For example, while auction theory may assume a centralized clearing house, there is no analog in a decentralized system seeking to avoid single points of failure or centralized policies. Similarly, game theory often assumes that each player is able to observe everyone else's actions, or at the very least know how many other players there are, but maintaining perfect system-wide information is impossible in most systems. In other words, not all incentive mechanisms are systems-compatible. The main contribution of this dissertation is the design, implementation, and evaluation of various systems-compatible incentive mechanisms and their application to a wide range of deployable systems. These systems include BitTorrent, which is used to distribute a large file to a large number of downloaders, PeerWise, which leverages user cooperation to achieve lower latencies in Internet routing, and Hoodnets, a new system I present that allows users to share their cellular data access to obtain greater bandwidth on their mobile devices. Each of these systems represents a different point in the design space of systems-compatible incentives. Taken together, along with their implementations and evaluations, these systems demonstrate that systems-compatibility is crucial in achieving practical incentives in real systems. I present design principles outlining how to achieve systems-compatible incentives, which may serve an even broader range of systems than considered herein. I conclude this dissertation with what I consider to be the most important open problems in aligning the competing interests of the Internet's participants

From resource allocation to neighbor selection in peer-to-peer networks

Incluye bibliografía y anexosEn la tesis se estudia primero, desde un punto de vista teórico, las diferentes posibilidades de asignación de recursos de las redes peer-to-peer (P2P) y los incentivos que las mismas proveen a los peers. Luego, se realiza el diseño de un algoritmo que alcanza la asignación deseada manteniendo los incentivos para motivar a los peers a contribuir. Analizando los incentivos aparece un compromiso entre eficiencia y justicia en la red. Se procede a diseñar un algoritmo descentralizado de “selección de vecinos” (donde se elige con quién compartir contenido de manera de alcanzar un óptimo global). El algoritmo se basa en el uso de Cadenas de Markov de tiempo continuo que aparecen en el estudio de la mecánica estadística, en particular las distribuciones de Gibbs. El algoritmo consiste en un Gibbs Sampler, que alcanza la asignación deseada manteniendo sencillez en la implementación. En la última parte de la tesis se extienden las propuestas al contexto de redes inalámbricas ad-hoc, en las cuales el compromiso de eficiencia y justicia cambia radicalmente debido a que la eficiencia de la red está asociada a qué vecinos podemos elegir para comunicar, ya que en las redes inalámbricas las restricciones de capacidad se vuelven par a par, en lugar de una única restricción de subida por peer. Las interferencias entre enlaces debido la comunicación inalámbrica complican aún más el problema. De todos modos, se propone una extensión al algoritmo que logra los objetivos deseados también en este tipo de redes y que permite modular el compromiso entre eficiencia y justicia satisfactoriamente.ANII - POS_NAC_2012_1_9088

BitTorrent is an Auction: Analyzing and Improving BitTorrent’s Incentives, in:

ABSTRACT Incentives play a crucial role in BitTorrent, motivating users to upload to others to achieve fast download times for all peers. Though long believed to be robust to strategic manipulation, recent work has empirically shown that BitTorrent does not provide its users incentive to follow the protocol. We propose an auction-based model to study and improve upon BitTorrent's incentives. The insight behind our model is that BitTorrent uses, not tit-for-tat as widely believed, but an auction to decide which peers to serve. Our model not only captures known, performance-improving strategies, it shapes our thinking toward new, effective strategies. For example, our analysis demonstrates, counter-intuitively, that BitTorrent peers have incentive to intelligently under-report what pieces of the file they have to their neighbors. We implement and evaluate a modification to BitTorrent in which peers reward one another with proportional shares of bandwidth. Within our game-theoretic model, we prove that a proportional-share client is strategy-proof. With experiments on PlanetLab, a local cluster, and live downloads, we show that a proportional-share unchoker yields faster downloads against BitTorrent and BitTyrant clients, and that underreporting pieces yields prolonged neighbor interest

Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

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

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

On the study of the optimistic unchoking algorithms and incentive mechanisms of BitTorrent

Optimistic unchoking plays an important role in BitTorrent Peer-to-Peer (P2P)[46, 45, 48, 4] file sharing networks. Peers use optimistic unchoking to find upload bandwidth information about their neighbors. However, free-riders can also take advantage of optimistic unchoking and download from the network without uploading anything. In this thesis, a novel optimistic unchoking algorithm for BitTorrent is proposed. The main purposes of our algorithm are to prevent free-riding and to improve the efficiency of optimistic unchoking. A stochastic model is then proposed to analyze the performance of my algorithm. We also verify the results by simulations. BitTorrent also have a built-in incentive mechanism called "Tit-for-Tat" [4] to prevent free-riding. Basically, a peer will upload to other peers (default is four) that give it the highest download rate. In this thesis, We will show that by adjusting the upload rate and the number of uploads, a selfish peer can take advantage of the "Tit-for-Tat" [4] to improve its download rate. However, this strategy of the selfish peer is harmful to the whole network. If many peers take the same strategy, the performance of the whole network will be significantly decreased. It is then theoretically proved that the "Tit-for-Tat" [4] is not an optimal incentive mechanism. To solve this problem, We propose a new incentive mechanism for BitTorrent. With this new mechanism, even if all peers are selfish, the performance of the whole network can still be maintained at a very high leve