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Peer-to-peer protocols play an increasingly instrumental role in Internet content distribution. Gains over decentralized schemes are even larger.
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Our results use traces from a BitTorrent client for Android devices to show that RLNC outperforms the next best scheme (fully centralized Reed-Solomon) not only by having a much lower probability of data loss, but by reducing storage requirements by up to 50% and reconstruction traffic by up to 40%. We compare our fully distributed RLNC approach to centralized (genie aided) and fully decentralized replication and Reed-Solomon mechanisms.
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Our goal is to characterize RLNC's guaranteed data integrity region in terms of the total number of storage devices that need to be available and stored data per device. In this highly dynamic context, random linear network coding (RLNC) provides an interesting solution. As a consequence, conventional erasure correction approaches are ill-suited for maintaining data integrity. This imposes new challenges on the design as the number of available nodes varies greatly over time and keeping track of the system's state becomes unfeasible. Given the large costs for maintaining and cooling large data centers, our work proposes and studies the feasibility of a fully decentralized systems that can store data even on unreliable and, sometimes, unavailable mobile devices. Conventional systems rely on static designs with a central control entity to oversee and control the repair process. The described measurement results enable to understand the mobile BitTorrent behavior in details and the proposed models can be used also as a base model for designing other mobile peer-to-peer services.ĭistributed storage solutions have become widespread due to their ability to store large amounts of data reliably across a network of unreliable nodes, by employing repair mechanisms to prevent data loss. This research can be considered as a pioneer work in the field of analyzing large peer-to-peer networks in modern mobile environments. Beside the several statistics on for instance the sizes of accessed torrents and download times, we present parametric estimation models for the number of peers for a given torrent, and for the rate of peers which can be successfully connected to. As the mobile devices have some special properties like processing power, energy, and bandwidth limitations, the behavior differs from the traditional desktop clients. The reports allow us to analyze the usage patterns typical for mobile torrent clients.
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This application is available for free and is a full featured torrent client. In this paper we analyze the anonymous reports provided by our Android based BitTorrent client called DrTorrent.