Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Looking up data in P2P systems
Communications of the ACM
Analyzing peer-to-peer traffic across large networks
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
P2P '01 Proceedings of the First International Conference on Peer-to-Peer Computing
Measuring and analyzing the characteristics of Napster and Gnutella hosts
Multimedia Systems
A content model for evaluating peer-to-peer searching techniques
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Peer-to-Peer Systems and Applications (Lecture Notes in Computer Science)
Peer-to-Peer Systems and Applications (Lecture Notes in Computer Science)
On unbiased sampling for unstructured peer-to-peer networks
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Evaluating the accuracy of captured snapshots by peer-to-peer crawlers
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
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In this paper, we address some of the problems such as dead searches, complexity in the study of network topology and network overloading that are associated with Gnutella and Gnutella-like Peer-to-Peer (P2P) networks. We use advanced heuristic parameters with information shuffling as a solution for them. We propose an advancement of Gnutella using the above-mentioned schemes. At a panoramic level, our work is founded on the following concepts: (a) Crawling the P2P networks to shuffle information, so that the knowledge is distributed over the whole network, and (b) Bringing the information within searchable hops of each network. These have been verified on a self-built P2P simulator, named PeerNS, which works on actual P2P network statistics and is, hence, very close to the actual scenario. The results obtained through simulation affirm that the nodes with extremely large number of dead searches benefit the most and are observed to have a sharp decrease in their dead search count after crawling a small part of the overall network.