Recovery in Distributed Systems Using Optimistic Message Logging and Checkpointing

Message logging and check pointing can provide fault tolerance in distributed systems in which all process communication is through messages. This paper presents a general model for reasoning about recovery in these systems. Using this model_ we prove that the set of recoverable system states that have occurred during any single execution of the system forms a lattice, and that therefore, there is always a unique maximum recoverable system state, which never decreases. Based on this model, we present an algorithm for determining this maximum recoverable state, and prove its correctness. Our algorithm utilizes all logged messages and checkpoints, and thus always finds the maximum recoverable state possible. Previous recovery methods using optimistic message logging and checkpointing have not considered the existing checkpoints, and thus may not find this maximum state. Furthermore, by utilizing the checkpoints, some messages received by a process before it was checkpointed may not need to be logged. Using our algorithm also adds less communication overhead to the system than do previous methods. Our model and algorithm can be used with any message logging protocol, whether pessimistic or optimistic, but their full generality is only required with optimistic logging protocols.