Dynamic replication factor model for Linux containers-based cloud systems

Infrastructure-as-a-service container-based virtualization is gaining interest as a platform for running distributed applications. With increasing scale of cloud architectures, faults are becoming a frequent occurrence, which makes availability true challenge. Replication is a method to survive failures whether of checkpoints, containers or data to increase their availability. In fact, following a node failure, fault-tolerant cloud systems restart failed containers on a new node from distributed images of containers (or checkpoints). With a high failure rate, we can lose some replicas. It is interesting to increase the replication factor in some cases and finding the trade-off between restarting all failed containers and storage overhead. This paper addresses the issue of adapting the replication factor and contributes with a novel replication factor modeling approach, which is able to predict the right replication factor using prediction techniques. These techniques are based on experimental modeling, which analyze collected data related to different executions. We have used regression technique to find the relation between availability and replicas number. Experiments on the Grid’5000 testbed demonstrate the benefits of our proposal to satisfy the availability requirement, using a real fault-tolerant cloud system.