Reliability-Based Software Rejuvenation Scheduling for Cloud-Based Systems

The reliability and availability of a cloud-based system play an important role in evaluating its system performance. Due to the promised high reliability of physical facilities provided for cloud services, software faults have become a major factor for failures of cloud-based systems. In this paper, we focus on the software aging phenomenon where system performance may be progressively degraded due to exhaustion of system resources, fragmentation and accumulation of errors. We present a proactive technique, called software rejuvenation, to counteract the software aging problem. The dynamic fault tree (DFT) formalism is adopted to model the system reliability before and during a software rejuvenation process in an aging cloud-based system. Then it is converted into Markov Chains to derive the system reliability function. We use a case study of a cloud-based system to illustrate the validity of our approach. Based on the reliability analysis results, we show how to estimate software rejuvenation schedules that can keep the system reliability above a predefined critical level for required system availability. Keywords-Software aging; software rejuvenation; reliability analysis; dynamic fault tree (DFT); Markov chain; scheduling.