Abstract
A common mechanism to improve availability and performance is checkpointing and rollback. When it is time to checkpoint, a system stores a job's state to nonvolatile memory, and, when a failure occurs, it rolls back to the latest stored state instead of restarting the job from the beginning, thus improving performance in the presence of failures. Too frequent checkpointing reduces the amount of work to be redone in case of failures but generates excessive overhead, degrading performance. This paper presents a novel and very efficient queuing network model that addresses software component contention for hardware resources and shows how it can be used to model checkpointing in heterogeneous component-based software systems. We validated this model against a previous model, developed by the authors, that used Markov Chains. Our new model is orders of magnitude faster than the previous one and can be used to plan for checkpointing at run-time. As an additional contribution of this paper, we present an optimizer to find, for each software component, the optimal checkpointing interval that minimizes execution time, maximizes availability, or minimizes checkpointing overhead. (c) 2018 Elsevier Inc. All rights reserved.