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)
GROUP MEMBERSHIP IN THE EPIDEMIC STYLE
GROUP MEMBERSHIP IN THE EPIDEMIC STYLE
Scalable message stability detection protocols
Scalable message stability detection protocols
A gossip-style failure detection service
Middleware '98 Proceedings of the IFIP International Conference on Distributed Systems Platforms and Open Distributed Processing
Exact probability distributions for peer-to-peer epidemic information diffusion
ACM SIGMETRICS Performance Evaluation Review
Stepwise fair-share buffering for gossip-based peer-to-peer data dissemination
Computer Networks: The International Journal of Computer and Telecommunications Networking
An analytical framework for self-organizing peer-to-peer anti-entropy algorithms
Performance Evaluation
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We consider peer-to-peer anti-entropy paradigms for epidemic information diffusion, namely pull, push and hybrid cases, and provide exact performance measures for them. Major benefits of the proposed epidemic algorithms are that they are fully distributed, utilize local information only via pair-wise interactions, and provide eventual consistency, scalability and communication topology-independence. Our contribution is the derivation of 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. In terms of these criteria, the hybrid approach outperforms pull and push paradigms, and push is better than the pull case. Such theoretical results would be beneficial when integrating the models in several peer-to-peer distributed application scenarios.