NDLI: A case for coalitions in data swarming systems

Content Provider	IEEE Xplore Digital Library
Author	Honggang Zhang Vasudevan, S. Ran Li Towsley, D.
Copyright Year	2011
Description	Author affiliation: Alcatel-Lucent Bell Labs, Murray Hill, NJ 07974 (Vasudevan, S.) \|\| Math & Computer Science Dept., Suffolk Univ., Boston, MA 02108 (Honggang Zhang; Ran Li) \|\| Computer Science Department, UMass Amherst, Amherst, MA 01003 (Towsley, D.)
Abstract	We present an argument in favor of forming coalitions of peers in a data swarming system consisting of peers with different upload capacities. A coalition is a set of peers with the same upload capacity that explicitly cooperate with other peers inside the coalition via choking and capacity allocation strategies. Further, each peer interacts with other peers outside its coalition via potentially distinct choking and capacity allocation strategies. This paper focuses on the efficiency of different choking strategies, assuming that peers do not share data with other peers outside their coalitions. We first develop an analytical model that accurately predicts the performance of a coalition of peers adopting BitTorrent's Tit-for-Tat choking strategy. Our model highlights a number of inefficiencies of Tit-for-Tat strategy. Accordingly, we propose a random choking strategy, and show that it can help a coalition achieve near-optimal performance and it significantly outperforms not only Tit-for-Tat strategy but also unchoke-all strategy. Using cooperative game theory, we prove the existence of stable coalitions, and demonstrate the convergence of the dynamic coalition formation process when peers use our cooperation-aware better response strategy. Using extensive simulations, we demonstrate significant performance benefits due to coalition formation.
Starting Page	246
Ending Page	255
File Size	571752
Page Count	10
File Format	PDF
ISBN	9781457713927
e-ISBN	9781457713941
DOI	10.1109/ICNP.2011.6089058
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-17
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Analytical models Resource management Equations Steady-state Data models Computational modeling
Content Type	Text
Resource Type	Article

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