Stochastic processes as concurrent constraint programs
Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Resource discovery in distributed networks
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
ACM Transactions on Computer Systems (TOCS)
Gossip versus Deterministically Constrained Flooding on Small Networks
DISC '00 Proceedings of the 14th International Conference on Distributed Computing
Ad Hoc Membership for Scalable Applications
DISC '02 Proceedings of the 16th International Conference on Distributed Computing
Throughput Stability of Reliable Multicast Protocols
ADVIS '00 Proceedings of the First International Conference on Advances in Information Systems
View Divergence Control of Replicated Data Using Update Delay Estimation
SRDS '99 Proceedings of the 18th IEEE Symposium on Reliable Distributed Systems
What service replication middleware can learn from object replication middleware
Proceedings of the 1st workshop on Middleware for Service Oriented Computing (MW4SOC 2006)
Replicating multithreaded web services
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
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We present a class of scalable and probabilisticly reliable communication protocols. The protocols are based on a probabilistic system model and thus their properties tend to be probabilistic in nature. The protocols are scalable in two senses. First, the message costs and latencies of the protocols grow slowly with the system size. Second, the reliability of the protocols, expressed in terms of the probability of a failed run of a protocol, approaches 0 exponentially fast as the number of processes is increased. This scalable reliability is achieved through a form of gossip protocol which is strongly self-stabilizing in a sense similar, although not identical to, the notion of self stabilizing systems proposed by Dijkstra.