Complexity of network synchronization
Journal of the ACM (JACM)
Repeated Computation of Global Functions in a Distributed Environment
IEEE Transactions on Parallel and Distributed Systems
Distributed Infimum Approximation
FCT '87 Proceedings of the International Conference on Fundamentals of Computation Theory
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Communication-efficient distributed monitoring of thresholded counts
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Scalable algorithms for global snapshots in distributed systems
Proceedings of the 20th annual international conference on Supercomputing
Communication-Efficient Tracking of Distributed Cumulative Triggers
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Echo Algorithms: Depth Parallel Operations on General Graphs
IEEE Transactions on Software Engineering
Algorithms for distributed functional monitoring
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
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Consider a distributed system with n processors, in which each processor receives some triggers from an external source. The distributed trigger counting problem is to raise an alert and report to a user when the number of triggers received by the system reaches w, where w is a user-specified input. The problem has applications in monitoring, global snapshots, synchronizers and other distributed settings. The main result of the paper is a decentralized and randomized algorithm with expected message complexity O(n log n log w). Moreover, every processor in this algorithm receives no more than O(log n log w) messages with high probability. All the earlier algorithms for this problem have maximum message load of Ω(n log w).