Peer-to-peer (P2P) overlay networks such as BitTorrent and Avalanche are increasingly used for disseminating potentially large files from a server to many end users via the Internet. The key idea is to divide the file into many equally-sized parts and then let users download each part (or, for network coding based systems such as Avalanche, linear combinations of the parts) either from the server or from another user who has already downloaded it. However, their performance evaluation has typically been limited to comparing one system relative to another and typically been realized by means of simulation and measurements. In contrast, we provide an analytic performance analysis that is based on a new uplink-sharing version of the well-known broadcasting problem. Assuming equal upload capacities, we show that the minimal time to disseminate the file is the same as for the simultaneous send receive version of the broadcasting problem. For general upload capacities, we provide a mixed integer linear program (MILP) solution and a complementary fluid limit solution. We thus provide a lower bound which can be used as a performance benchmark for any P2P file dissemination system. We also investigate the performance of a decentralized strategy, providing evidence that the performance of necessarily decentralized P2P file dissemination systems should be close to this bound and therefore that it is useful in practice.
Slurpie @cite_24 is a very similar protocol, although, unlike BitTorrent, it does not fix the number of neighbours and it adapts to varying bandwidth conditions. Other P2P overlay networks have also been proposed. For example see SplitStream @cite_32 and Bullet' @cite_22 .
@cite_24 @cite_22 @cite_32
2135039403 2065185800 2153388671 2144334146
We present Slurpie: a peer-to-peer protocol for bulk data transfer. Slurpie is specifically designed to reduce client download times for large, popular files, and to reduce load on servers that serve these files. Slurpie employs a novel adaptive downloading strategy to increase client performance, and employs a randomized backoff strategy to precisely control load on the server. We describe a full implementation of the Slurpie protocol, and present results from both controlled local-area and wide-area testbeds. Our results show that Slurpie clients improve performance as the size of the network increases, and the server is completely insulated from large flash crowds entering the Slurpie network. BitTorrent is probably the most famous file-sharing protocol used in the Internet currently. It represents more than half of the P2P traffic. Various applications are using BitTorrent-like protocols to deliver the resource and implement techniques to perform a reliable data transmission. Forward Error Correction (FEC) is an efficient mechanism used for this goal. This paper proposes a performance evaluation of FEC implemented on BitTorrent protocol. A simulation framework has been developed to evaluate the improvement depending on many factors like the leeches seeds number and capacities, the network nature (homogeneous or heterogeneous), the resource size, and the FEC redundancy ratio. The completion time metric shows that FEC is a method that accelerates the data access in some specific network configurations. On the contrary, this technique can also disrupt the system in some cases since it introduces an overhead. BitTorrent, one of the most widespread file sharing P2P applications, recently introduced uTP, an application-level congestion control protocol which aims to efficiently use the available link capacity, while avoiding to interfere with the rest of user traffic (e.g., Web, VoIP and gaming) sharing the same access bottleneck. Research on uTP has so far focused on the investigation of the congestion control behavior on rather simple settings (i.e., single bottleneck, few backlogged flows, etc.), that are fairly far from the P2P settings in which the protocol is deployed. Moreover, prior work typically addressed questions, such as fairness and efficiency, that are natural from a congestion control context perspective, but are not directly related with the performance of the overall P2P system. In this work, we refine the understanding of uTP, by gauging its impact on the primary BitTorrent user-centric metric, namely the torrent download time, by means of packet level simulation. Results of our initial investigations show that: (i) in case uTP clients fully substitute TCP clients, no performance difference arise; (ii) in case of heterogeneous swarms, comprising peers using uTP and TCP congestion control, completion time of uTP peers can possibly benefit of lower uplink queuing delays, as signaling traffic (e.g., chunk requests) are not slowed down by long waits in the ADSL buffers. 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 BitTorrent's 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 BitTorrent's well-known ‘tit-for-tat’ mechanism in bandwidth-inhomogeneous swarms and provides an accurate mathematical description of the resulting dynamics.