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SIAM Journal on Computing
Epidemic algorithms in replicated databases (extended abstract)
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Bayeux: an architecture for scalable and fault-tolerant wide-area data dissemination
NOSSDAV '01 Proceedings of the 11th international workshop on Network and operating systems support for digital audio and video
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Informed content delivery across adaptive overlay networks
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Peer-to-Peer Membership Management for Gossip-Based Protocols
IEEE Transactions on Computers
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
Lightweight Probabilistic Broadcast
DSN '01 Proceedings of the 2001 International Conference on Dependable Systems and Networks (formerly: FTCS)
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Dynamic Programming
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ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
SplitStream: high-bandwidth multicast in cooperative environments
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
The peer sampling service: experimental evaluation of unstructured gossip-based implementations
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
PeerWindow: An Efficient, Heterogeneous, and Autonomic Node Collection Protocol
ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
Maintaining high bandwidth under dynamic network conditions
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Democratizing content publication with coral
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Structure management for scalable overlay service construction
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Using random subsets to build scalable network services
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
The julia content distribution network
WORLDS'05 Proceedings of the 2nd conference on Real, Large Distributed Systems - Volume 2
Compact samples for data dissemination
ICDT'07 Proceedings of the 11th international conference on Database Theory
Scribe: a large-scale and decentralized application-level multicast infrastructure
IEEE Journal on Selected Areas in Communications
Journal of Computer and System Sciences
Mobile Peer-to-Peer data dissemination in wireless ad-hoc networks
Information Sciences: an International Journal
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We consider data dissemination in a peer-to-peer network, where each user wishes to obtain some subset of the available information objects. In most of the modern algorithms for such data dissemination, the users periodically obtain samples of peer IDs (possibly with some summary of their content). They then use the samples for connecting to other peers and downloading data pieces from them. For a set O of information objects, we call a sample of peers, containing at least k possible providers for each object o@?O, a k-sample. In order to balance the load, the k-samples should be fair, in the sense that for every object, its providers should appear in the sample with equal probability. Also, since most algorithms send fresh samples frequently, the size of the k-samples should be as small as possible, to minimize communication overhead. We describe in this paper two novel techniques for generating fair and small k-samples in a P2P setting. The first is based on a particular usage of uniform sampling and has the advantage that it allows to build on standard P2P uniform sampling tools. The second is based on non-uniform sampling and requires more particular care, but is guaranteed to generate the smallest possible fair k-sample. The two algorithms exploit available dependencies between information objects to reduce the sample size, and are proved, both theoretically and experimentally, to be extremely effective.