A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
The IceCube approach to the reconciliation of divergent replicas
Proceedings of the twentieth annual ACM symposium on Principles of distributed computing
Early measurements of a cluster-based architecture for P2P systems
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
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
Location Awareness in Unstructured Peer-to-Peer Systems
IEEE Transactions on Parallel and Distributed Systems
Dynamic and distributed reconciliation in P2P-DHT networks
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
Tapestry: a resilient global-scale overlay for service deployment
IEEE Journal on Selected Areas in Communications
Scalable and topology-aware reconciliation on P2P networks
Distributed and Parallel Databases
Flower-CDN: a hybrid P2P overlay for efficient query processing in CDN
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Locaware: index caching in unstructured P2P-file sharing systems
Proceedings of the 2009 EDBT/ICDT Workshops
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A growing number of collaborative applications are being built on top of Peer-to-Peer (P2P) networks which provide scalability and support dynamic behavior. However, the distributed algorithms used by these applications typically introduce multiple communications and interactions between nodes. This is because P2P networks are constructed independently of the underlying topology, which may cause high latencies and communication overheads. In this paper, we propose a topologyaware approach that exploits physical topology information to perform P2P distributed data reconciliation, a major function for collaborative applications. Our solution (P2P-Reconciler-TA) relies on dynamically selecting nodes to execute specific steps of the algorithm, while carefully placing relevant data. We show that P2P-Reconciler-TA introduces a gain of 50% compared to P2P-Reconciler and still scales up.