Analyzing peer-to-peer traffic across large networks
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Improving Traffic Locality in BitTorrent via Biased Neighbor Selection
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Characterizing unstructured overlay topologies in modern P2P file-sharing systems
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Can ISPS and P2P users cooperate for improved performance?
ACM SIGCOMM Computer Communication Review
Taming the torrent: a practical approach to reducing cross-isp traffic in peer-to-peer systems
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
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In this paper, we apply the theory predicting neighbor distribution of arbitrary random graphs to analyze the network coverage of the peers in unstructured peer-to-peer(p2p) networks that use TTL -based flooding mechanism for search and query. However, we find that for many cases, the theory cannot be directly applied to obtain correct estimate of network coverage due to the presence of certain types of edges that we refer as cross and back edges. It is also observed that the presence of cross and back edges in the p2p networks reduce the coverage of the peers and also generates large number of redundant messages, thus wasting precious bandwidth. We refine the theory and develop a model to estimate the network coverage of the peers in the presence of cross and back edges. We simulate our model for different networks with various degree distribution properties. The results indicate that our models provide good estimates of second neighbor and network coverage distribution. We perform a case study of the Gnutella networks to analyze the effects cross and back edges on network coverage and message complexity in these networks. Based on our study, we propose a new bootstrapping algorithm for Gnutella networks named HPC5 that substantially improves the network coverage and message complexity. The results have been validated using simulations.