TY - GEN
T1 - The hidden locality in swarms
AU - Otto, John S.
AU - Bustamante, Fabian E
PY - 2013
Y1 - 2013
N2 - People use P2P systems such as BitTorrent to share an unprecedented variety and amount of content with others around the world. The random connection pattern used by BitTorrent has been shown to result in reduced performance for users and costly cross-ISP traffic. Although several client-side systems have been proposed to improve the locality of BitTorrent traffic, their effectiveness is limited by the availability of local peers. We show that sufficient locality is present in swarms - if one looks at the right time. We find that 50% of ISPs have at least five local peers online during the ISP's peak hour, typically in the evening, compared to only 20% of ISPs during the median hour. To better discover these local peers, we show how to increase the overall peer discovery rate by over two orders of magnitude using client-side techniques: leveraging additional trackers, requesting more peers per sample, and sampling more frequently. We propose an approach to predict future availability of local peers based on observed diurnal patterns. This approach enables peers to selectively apply these techniques to minimize undue load on trackers.
AB - People use P2P systems such as BitTorrent to share an unprecedented variety and amount of content with others around the world. The random connection pattern used by BitTorrent has been shown to result in reduced performance for users and costly cross-ISP traffic. Although several client-side systems have been proposed to improve the locality of BitTorrent traffic, their effectiveness is limited by the availability of local peers. We show that sufficient locality is present in swarms - if one looks at the right time. We find that 50% of ISPs have at least five local peers online during the ISP's peak hour, typically in the evening, compared to only 20% of ISPs during the median hour. To better discover these local peers, we show how to increase the overall peer discovery rate by over two orders of magnitude using client-side techniques: leveraging additional trackers, requesting more peers per sample, and sampling more frequently. We propose an approach to predict future availability of local peers based on observed diurnal patterns. This approach enables peers to selectively apply these techniques to minimize undue load on trackers.
UR - http://www.scopus.com/inward/record.url?scp=84893290450&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893290450&partnerID=8YFLogxK
U2 - 10.1109/P2P.2013.6688713
DO - 10.1109/P2P.2013.6688713
M3 - Conference contribution
AN - SCOPUS:84893290450
SN - 9781479905218
T3 - 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings
BT - 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings
PB - IEEE Computer Society
T2 - 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013
Y2 - 9 September 2013 through 11 September 2013
ER -