Michel Meulpolder

Give-to-Get : free-riding resilient video-on-demand in P2P systems

Centralised solutions for Video-on-Demand (VoD) services, which stream pre-recorded video content to multiple clients who start watching at the moments of their own choosing, are not scalable because of the high bandwidth requirements of the central video servers. Peer-to-peer (P2P) techniques which let the clients distribute the video content among themselves, can be used to alleviate this problem. However, such techniques may introduce the problem of free-riding, with some peers in the P2P network not forwarding the video content to others if there is no incentive to do so. When the P2P network contains too many free-riders, an increasing number of the well-behaving peers may not achieve high enough download speeds to maintain an acceptable service. In this paper we propose Give-to-Get, a P2P VoD algorithm which discourages free-riding by letting peers favour uploading to other peers who have proven to be good uploaders. As a consequence, free-riders are only tolerated as long as there is spare capacity in the system. Our simulations show that even if 20% of the peers are free-riders, Give-to-Get continues to provide good performance to the well-behaving peers. In particular, they show that Give-to-Get performs very well for short videos, which dominate the current VoD traffic on the Internet.

Improving Efficiency and Fairness in P2P Systems with Effort-Based Incentives

Most P2P systems that have some kind of incentive mechanism reward peers according to their contribution, i.e. total bandwidth offered to the system. Due to the disparity in bandwidth capacity between P2P users on the Internet, the common effect of such mechanisms is that the fastest peers reap the highest benefits. We take a different approach and study how to incentivize cooperation in P2P systems based on effort, i.e. contribution relative to capacity. We make the following contributions: 1) we argue that contribution-based incentive schemes in P2P systems unnecessarily disfavor slow peers and decrease overall system performance; 2) we advocate the use of principles from an alternative economic vision, Participatory Economics (Parecon), to inspire systems to be fair and to ensure maximization of the social welfare while being efficient at the same time, and 3) we present the results of simulations in which we apply principles from Parecon to two popular real life systems: a) the popular file sharing BitTorrent protocol; b) a generic credit based sharing ratio enforcement scheme. Our approach yields a higher system performance and fairness and offers new insights into P2P incentive design.

Modeling and analysis of bandwidth-inhomogeneous swarms in BitTorrent

A number of analytical models exists that capture various properties of the BitTorrent protocol. However, until now virtually all of these models have been based on the assumption that the peers in the system have homogeneous bandwidths. As this is highly unrealistic in real swarms, these models have very limited applicability. Most of all, these models implicitly ignore BitTorrents most important property: peer selection based on the highest rate of reciprocity. As a result, these models are not suitable for understanding or predicting the properties of real BitTorrent networks. Furthermore, they are hardly of use in the design of realistic BitTorrent simulators and new P2P protocols. In this paper, we extend existing work by presenting a model of a swarm in BitTorrent where peers have arbitrary upload and download bandwidths. In our model we group peers with (roughly) the same bandwidth in classes, and then analyze the allocation of upload slots from peers in one class to peers in another class. We show that our model accurately predicts the bandwidth clustering phenomenon observed experimentally in other work, and we analyze the resulting data distribution in swarms. We validate our model with experiments using real BitTorrent clients. Our model captures the effects of BitTorrents well-known ‘tit-for-tat’ mechanism in bandwidth-inhomogeneous swarms and provides an accurate mathematical description of the resulting dynamics.

Modeling and analyzing the effects of firewalls and NATs in P2P swarming systems

Many P2P systems have been designed without taking into account an important factor: a large fraction of Internet users nowadays are located behind a network address translator (NAT) or a firewall, making them unable to accept incoming connections (i.e. unconnectable). Peers suffering from this limitation cannot fully enjoy the advantages offered by the P2P architecture and thus they are likely to get a poor performance. In this work, we present a mathematical model to study the performance of a P2P swarming system in the presence of unconnectable peers.We quantify the average download speeds of peers and find that unconnectable peers achieve a lower average download speed compared to connectable peers, and this difference increases hyperbolically as the percentage of unconnectable peers grows. More interestingly, we notice that connectable peers actually benefit from the existence of peers behind NATs/firewalls, since they alone can enjoy the bandwidth that those peers offer to the system. Inspired by these observations, we propose a new policy for the allocation of the systems bandwidth that can mitigate the performance issues of unconnectable peers. In doing so, we also find an intrinsic limitation in the speed improvement that they can possibly achieve.

The problem of upload competition in peer‐to‐peer systems with incentive mechanisms

As peer‐to‐peer (P2P) file‐sharing systems revolve around cooperation, the design of upload incentives has been one of the most important topics in P2P research for more than a decade. Several deployed systems, such as private BitTorrent communities, successfully manage to foster cooperation by banning peers when their sharing ratio becomes too low. Interestingly, recent measurements have shown that such systems tend to have an oversupply instead of an undersupply of bandwidth designers that have been obsessed with since the dawn of P2P. In such systems, the ‘selfish peer’ problem is finally solved, but a new problem has arisen: because peers have to keep up their sharing ratios, they now have to compete to upload. In this paper, we explore this new problem and show how even highly cooperative peers might in the end not survive the upload competition. On the basis of recent measurements of over half a million peers in private P2P communities, we propose and analyze several algorithms for uploader selection under oversupply. Our algorithms enable sustained sharing ratio enforcement and are easy to implement in both existing and new systems. Overall, we offer an important design consideration for the new generation of P2P systems in which selfishness is no longer an issue. Copyright

Replication in bandwidth-symmetric BitTorrent networks

The popular and well-known BitTorrent peer-to-peer protocol offers fast file distribution in a highly scalable way. Several studies have investigated the properties of this protocol, mostly focusing on heterogeneous end-user environments such as the Internet, with asymmetric connections. In this paper however, we focus on the usage of the BitTorrent protocol in homogeneous local environments with symmetric bandwidth properties. Compared with a traditional client-server setup, the use of BitTorrent in such settings can offer huge benefits in performance and scalability, allowing bandwidth sharing and high speed file distribution. We aim to improve the performance of such networks with a novel mechanism for replication using so-called replicators, which replicate a subset of the files in the system. A mathematical model of the resulting Replicated BitTorrent is presented and validated by emulation. Furthermore, we present simulation results that provide insight in the performance of Replicated BitTorrent networks with dynamic peer arrivals and departures. The results show that Replicated BitTorrent significantly improves download times in local bandwidth-symmetric BitTorrent networks.

Modeling and Analysis of Sharing Ratio Enforcement in Private BitTorrent Communities

Providing incentives for user contribution has been one of the primary design goals of Peer-to-Peer systems. The newly-emerged BitTorrent private communities adopt Sharing Ratio Enforcement (SRE) on top of BitTorrents incentive mechanism, Tit-For-Tat, in order to strictly enforce a minimum contribution a member has to provide, in relation to the amount of service it has received. In this paper, we provide a theoretical model to analyze 1) how SRE provides seeding incentives, and 2) how SRE influences the download performance in the system. Specifically, we study the influence of the SRE threshold (i.e., the minimum sharing ratio requirement) and the bandwidth heterogeneity of the peers in the system. In our analysis, we assume users to be rational, i.e., peers seed only the minimum amount required by SRE, and we show that the download performance as predicted by our model represents a lower bound for the actual performance that can be reached in a BitTorrent private community. Hence, following our model, community administrators can predict the minimum performance level their systems will be able to reach.

Robust vote sampling in a P2P media distribution system

The explosion of freely available media content through BitTorrent file sharing networks over the Internet means that users need guides or recommendations to find the right, high quality, content. Current systems rely on centralized servers to aggregate, rate and moderate metadata for this purpose. We present the design and simulations, using real BitTorrent traces, for a method combining fully decentralized metadata dissemination, vote sampling and ranking for deployment in the Tribler.org BitTorrent media client. Our design provides robustness to spam attacks, where metadata does not reflect the content it is attached to, by controlling metadata spreading and by vote sampling based on a collusion proof experience function. Our design is light-weight, fully decentralized and offers good performance and robustness under realistic conditions.