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BiToS: Enhancing BitTorrent for Supporting Streaming Applications

BiToS (BitTorrent Streaming) is a modified BitTorrent protocol designed to support streaming applications. It introduces a variable size sliding time window for piece selection, improving timeliness of arrival and enabling better support for live video streaming. This research paper evaluates the performance of BiToS using a BitTorrent simulator and concludes that the rarest-first policy within the high priority set yields the best results.

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BiToS: Enhancing BitTorrent for Supporting Streaming Applications

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  1. BiToS: Enhancing BitTorrent for SupportingStreaming Applications Aggelos VlavianosMarios Iliofotou Michalis Faloutsos University of California Riverside

  2. What is BiToS • BiToS = BitTorrent Streaming • A BT-based protocol with the ability to support streaming • Modifies the piece selection policy of BT and nothing else • Uses a variable size sliding time window

  3. BitTorrent • I skipped this part

  4. Related Work • Bass (2005) • Hybrid server/P2P streaming system • Uses an almost unmodified version of BT • CoolStreaming • Uses a fixed sliding time window • Chainsaw • Uses gossip and push-based approaches

  5. BitTorrent Limitations • Piece selection mechanism • Based on rarity • Neglects deadlines • Poorly suited to Live Video Streaming • Would have to redesign the tracker • Can be tuned to support Playback Video Streaming

  6. BiToS

  7. Received pieces • State of a piece can be • Downloaded • Not-Downloaded • Missed (too late!)

  8. High priority set • Contains pieces that are • Not downloaded yet • Not missed • Close to be reproduced by the player • Set has a fixed size • BiToS parameter

  9. Remaining pieces set • Contains pieces that are • Not Downloaded • Not Missed • Not in the High Priority Set

  10. Selection process • Peer select with probability • p to select a piece in its High Priority Set • 1 – p to select a piece in the remaining pieces set • Piece selection is rarest first • When a piece from the High Priority Set is downloaded, it is replaced in that set by the first piece in sequence from the Remaining Pieces Set

  11. Timeliness of Arrival • Pieces that cannot meet playback deadlines are marked Missed

  12. The effect of probability p • p = 1 means that the peer will only download pieces that are in the High Priority Set • Peer will have the pieces it needs • Not clear that these pieces will be in high demand by other peers • Everyone is likely to have them • Peer may have problems later trading pieces with other peers

  13. The effect of probability p • p < 1 means that the peer will also download pieces that are not in its High Priority Set • Will be in the Remaining Pieces Set • Will be less likely to have been downloaded by too many peers • Can be traded later for other pieces

  14. Experimental evaluation • BitTorrent simulator • 4 seeders • 400 peers arriving in flash crowd • Ten minute video at 500 Kb/s • Upload and download rates are equal • 500 Kb/s

  15. Experimental results • Simulated three piece selection mechanisms • Sequential order within HPS and p = 1 • Rarest-first order within HPS and p = 1 • Rarest-first order within HPS and p = 0.8 • Use Continuity Index as benchmark

  16. Experimental results

  17. Experimental results

  18. Conclusions • Sliding time windows work! • Best sliding time window size is 5-10 percent of file size • Rarest-first policy outperforms sequential policy by a wide margin

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