SIAM Journal on Applied Mathematics
Epidemic algorithms for replicated database maintenance
PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
Providing high availability using lazy replication
ACM Transactions on Computer Systems (TOCS)
ACM Transactions on Computer Systems (TOCS)
Grapevine: an exercise in distributed computing
Communications of the ACM
ACM Transactions on Computer Systems (TOCS)
Probabilistic Reliable Dissemination in Large-Scale Systems
IEEE Transactions on Parallel and Distributed Systems
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
GROUP MEMBERSHIP IN THE EPIDEMIC STYLE
GROUP MEMBERSHIP IN THE EPIDEMIC STYLE
Scalable message stability detection protocols
Scalable message stability detection protocols
Lightweight probabilistic broadcast
ACM Transactions on Computer Systems (TOCS)
ACM Transactions on Computer Systems (TOCS)
Optimal scheduling of peer-to-peer file dissemination
Journal of Scheduling
A gossip-style failure detection service
Middleware '98 Proceedings of the IFIP International Conference on Distributed Systems Platforms and Open Distributed Processing
Exact performance measures for peer-to-peer epidemic information diffusion
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Gossiping With Multiple Messages
IEEE Transactions on Information Theory
ProFID: Practical frequent items discovery in peer-to-peer networks
Future Generation Computer Systems
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An analytical framework is developed for establishing exact performance measures for peer-to-peer (P2P) anti-entropy paradigms used in biologically inspired epidemic data dissemination. Major benefits of these paradigms are that they are fully distributed, self-organizing, utilize local data only via pair-wise interactions, and provide eventual consistency, reliability and scalability. We derive exact expressions for infection probabilities through elaborated counting techniques on a digraph. Considering the first passage times of a Markov chain based on these probabilities, we find the expected message delay experienced by each peer and its overall mean as a function of initial number of infectious peers. Further delay and overhead analysis is given through simulations and the analytical framework. The number of contacted peers at each round of the anti-entropy approach is an important parameter for both delay and overhead. These exact performance measures and theoretical results would be beneficial when utilizing the models in several P2P distributed system and network services such as replicated servers, multicast protocols, loss recovery, failure detection and group membership management.