Optimistic recovery in distributed systems
ACM Transactions on Computer Systems (TOCS)
Recovery in distributed systems using asynchronous message logging and checkpointing
PODC '88 Proceedings of the seventh annual ACM Symposium on Principles of distributed computing
Efficient distributed recovery using message logging
Proceedings of the eighth annual ACM Symposium on Principles of distributed computing
Recovery in distributed systems using optimistic message logging and check-pointing
Journal of Algorithms
Restoring consistent global states of distributed computations
PADD '91 Proceedings of the 1991 ACM/ONR workshop on Parallel and distributed debugging
Fail-stop processors: an approach to designing fault-tolerant computing systems
ACM Transactions on Computer Systems (TOCS)
Byzantine generals in action: implementing fail-stop processors
ACM Transactions on Computer Systems (TOCS)
An Efficient Protocol for Checkpointing Recovery in Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Garbage Collection in a Distributed Object-Oriented System
IEEE Transactions on Knowledge and Data Engineering
Efficient Algorithms for Crash Recovery in Distributed Systems
Proceedings of the Tenth Conference on Foundations of Software Technology and Theoretical Computer Science
Publishing: a reliable broadcast communication mechanism
SOSP '83 Proceedings of the ninth ACM symposium on Operating systems principles
Garbage collection in a causal message logging protocol
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
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Distributed systems use optimistic message logging for recovery from transient process failures. Such a recovery is facilitated by asynchronous message logging and check-pointing. It is also supported by garbage collection which requires identifying messages in stable storage that are no longer needed for the process of recovery. For this purpose, it is necessary to keep track of message dependencies between process states. A model to keep track of state dependencies using dependency graphs has been proposed.