Distributed recovery with K-optimistic logging
Journal of Parallel and Distributed Computing
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Message logging is a popular technique for building low-overhead protocols that tolerate process crash failures. Past research in message logging has focused on studying the relative overhead imposed by pessimistic, optimistic, and causal protocols during failure-free executions. In this paper, we give the first experimental evaluation of the performance of these protocols during recovery. We discover that, if a single failure is to be tolerated, pessimistic and causal protocols perform best, because they avoid rollbacks of correct processes. For multiple failures, however, the dominant factor in determining performance becomes where the recovery information is logged (i.e. at the sender, at the receiver, or replicated at a subset of the processes in the system) rather than when this information is logged (i.e. if logging is synchronous or asynchronous). From our results, we distil a few lessons that can guide the design of message-logging protocols that combine low-overhead during failure-free executions with fast recovery.