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IMC '05, 2005 Internet Measurement Conference — Abstract
Pp. 35–48 of the Proceedings
Measurements, Analysis, and Modeling of BitTorrent-like Systems
Lei Guo, College of William and Mary; Songqing Chen, George Mason University; Zhen Xiao, AT&T Labs—Research; Enhua Tan, Xiaoning Ding, and Xiaodong Zhang, College of William and Mary
Abstract
Existing studies on BitTorrent systems are single-torrent based, while more than 85% of all peers participate in multiple torrents according to our trace analysis. In addition, these studies are not sufficiently insightful and accurate even for single-torrent models, due to some unrealistic assumptions. Our analysis of representative BitTorrent traffic provides several new findings regarding the limitations of BitTorrent systems: (1) Due to the exponentially decreasing peer arrival rate in reality, service availability in such systems becomes poor quickly, after which it is difficult for the file to be located and downloaded. (2) Client performance in the BitTorrent-like systems is unstable, and fluctuates widely with the peer population. (3) Existing systems could provide unfair services to peers, where peers with high downloading speed tend to download more and upload less. In this paper, we study these limitations on torrent evolution in realistic environments. Motivated by the analysis and modeling results, we further build a graph based multi-torrent model to study inter-torrent collaboration. Our model quantitatively provides strong motivation for inter-torrent collaboration instead of directly stimulating seeds to stay longer. We also discuss a system design to show the feasibility of multi-torrent collaboration.
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