Analytic Models of Checkpointing for Concurrent Component-Based Software Systems.

Checkpointing and rollback is a key mechanism used to improve the reliability of software systems. The benefits of this mechanism can be offset by the overhead of checkpointing when the failure rate is low. The problem of developing analytic models of rollback and checkpointing has been continuously addressed for over four decades using different assumptions. This paper examines the problem under a more realistic angle, i.e., one in which there are several software components sharing resources (e.g., processors and I/O devices) among themselves and with the checkpointing processes. Additionally, the paper allows for different components to have different computing, rollback, and checkpointing demands, as well as different failure distributions. Our models also allow for various checkpointing processes to be executing concurrently to checkpoint the state of different software components. The analytic models developed here combine Markov Chains and Queuing Networks and allow us to compute the following metrics: (1) average time needed by a component to complete its execution, (2) average throughput of a component, (3) availability of a component, and (4) checkpointing overhead. The models were validated through extensive simulation and experimentation.