A Recovery Conscious Framework for Fault Resilient Storage Systems

In this paper we present a recovery-conscious framework for improving the fault resiliency and recovery efficiency of highly concurrent embedded storage software systems. Our frame-work consists of a three-tier architecture and a suite of recovery conscious techniques. In the top tier, we promote fine-grained recovery at the task level by introducing recovery groups to model recovery dependencies between tasks. At the middle tier we develop highly effective mappings of dependent tasks to pro-cessor resources through careful tuning of recovery efficiency sensitive parameters. At the bottom tier, we advocate the use of recovery-conscious scheduling by careful serialization of de-pendent tasks, which provides high recovery efficiency without sacrificing system performance. We develop a formal model to guide the understanding and the development of techniques for effectively mapping fine-grained tasks to system resources, aiming at reducing the ripple effect of software failures while sustaining high performance even during system recovery. Our techniques have been implemented on a real industry-standard storage system. Experimental results show that our techniques are effective, non-intrusive and can significantly boost system resilience while delivering high performance