Dynamic viewing pattern exploitation in Peer-to-Peer Video-on-Demand

Koravos, Filippos

doi:10.1109/ccnc.2011.5766537

Cited by 1 publication

(1 citation statement)

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“…While it is not the first work to add push operations to BitTorrent-like networks, it is the first to employ push in such manner, directly linking it to random seeks. A preliminary evaluation of the proposed scheme was presented in [1], while a full evaluation is presented in this work.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Uplink allocation based on user actions for peer-to-peer Video-on-Demand

Koravos

2014

2014 International Conference on Computing, Networking and Communications (ICNC)

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For more than a decade peer-to-peer networking technologies have met with huge success among Internet users, with peer-to-peer traffic already accounting for the largest part of the Internet's total traffic. Peer-to-peer networks have been extensively studied in recent years as an important supporting technology for state-of-the art applications, such as Live Video Streaming and Video-on-Demand. In this work the case of videoon-demand applications over BitTorrent-like unstructured peerto-peer networks is considered. As a rule, unstructured peerto-peer networks are pull-based, whereas push-based operation has been associated mostly with structured, tree-based p2p network topologies. While earlier studies maintained the pullbased nature of unstructured networks, recent ones have been investigating the combined use of pull and push operations, aiming at making more efficient use of the available bandwidth. Inspired by such hybrid approaches, this paper proposes a different use for push/pull protocols, uplink allocation based on user actions (i.e. random seek behavior) in video-on-demand applications. In a nutshell, this work proposes the employment of user-triggered push operations to prioritize content pre-fetching for the seemingly more popular parts for the users watching a video, thus increasing replication of such parts across the swarm.

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Section: Introduction and Related Workmentioning

confidence: 99%