Design and Analysis of Coalitions in Data Swarming Systems
Honggang Zhang, Sudarshan Vasudevan

TL;DR
This paper presents a comprehensive analysis and design of coalition mechanisms in data swarming systems, demonstrating how strategic cooperation among peers improves performance, data availability, and convergence in peer-to-peer networks.
Contribution
It introduces an analytical model for coalition strategies, proposes a data replication method, and demonstrates performance benefits through extensive simulations.
Findings
Random choking strategy predicts coalition performance accurately.
Optimal re-choking intervals and unchoke slots enhance coalition efficiency.
Data replication improves data availability significantly.
Abstract
We design and analyze a mechanism for forming coalitions of peers in a data swarming system where peers have heterogeneous upload capacities. A coalition is a set of peers that explicitly cooperate with other peers inside the coalition via choking, data replication, and capacity allocation strategies. Further, each peer interacts with other peers outside its coalition via potentially distinct choking, data replication, and capacity allocation strategies. Following on our preliminary work in IEEE ICNP 2011 that demonstrated significant performance benefits of coalitions, we present here a comprehensive analysis of the choking and data replication strategies for coalitions. We first develop an analytical model to understand a simple random choking strategy as a within-coalition strategy and show that it accurately predicts a coalition's performance. Our analysis formally shows that the…
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Taxonomy
TopicsPeer-to-Peer Network Technologies · Caching and Content Delivery · Game Theory and Applications
