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
ACM Transactions on Computer Systems (TOCS)
Monitoring and early warning for internet worms
Proceedings of the 10th ACM conference on Computer and communications security
On the performance of internet worm scanning strategies
Performance Evaluation
Exact performance measures for peer-to-peer epidemic information diffusion
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
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An efficient approach for information diffusion in distributed systems is to utilize epidemic algorithms that involve pair-wise propagation of updates. Epidemic algorithms are fully distributed and randomized approaches such that every peer in an information diffusion session picks a (subset of the other) peer(s) randomly for efficient propagation of updates, through periodic rounds. The underlying epidemics theory for the biological systems studies the spreading of infectious diseases through a population [1,2]. When applied to an information diffusion application, such protocols have beneficial features such as scalability, robustness against failures and provision of eventual consistency. Exact as well as asymptotical distributions have been studied for different epidemic models in [3,4]. In contrast to such previous studies, we investigate variations of the epidemic algorithms used in the context of distributed information diffusion and derive exact diffusion probabilities for them.