How to Recover Efficiently and Asynchronously when Optimism Fails

We propose a new algorithm for recovering asynchronously from failures in a distributed computation. Our algorithm is based on two novel concepts - a fault-tolerant vector clock to maintain causality information in spite of failures, and a history mechanism to detect orphan states and obsolete messages. These two mechanisms together with checkpointing and message-logging are used to restore the system to a consistent state after a failure of one or more processes. Our algorithm is completely asynchronous. It handles multiple failures, does not assume any message ordering, causes the minimum amount of rollback and restores the maximum recoverable state with low overhead. Earlier optimistic protocols lack one or more of the above properties