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Recently there has been renewed interest in building reliable servers that support continuous application operation. Besides maintaining system state consistent after a failure, one of the main challenges in achieving continuous operation is to provide fast reconfiguration. The complexity of the failure reconfiguration mechanisms employed and their overheads depend on the type of platform that is being used as a server and the types of applications that need to be supported. In this paper we focus on providing support for shared-memory applications running on clusters of commodity nodes and interconnects. Achieving continuous operation for shared memory applications on clusters presents two main challenges. (a) The fault tolerance mechanisms employed should be transparent to applications and should have low overhead during failure-free execution. (b) When failures occur, reconfiguration should occur with minimum application disruption without requiring the full recovery of the failed node.In this work we examine in detail the latter, i.e., (b), the failure reconfiguration path. We use a previously developed system [8] that achieves (a) by using dynamic replication of data to the memories of multiple nodes of the system during execution. We examine in detail how the runtime system can achieve minimum application interruption, when failures occur. We present the design and implementation of FineFRC (Fine-grained Failure Recon guration on Clusters), a runtime system for achieving continuous operation of shared memory applications on commodity clusters without requiring application instrumentation or human intervention. We present results using a working, 16-processor system that achieves sub-second failure reconfiguration times.

Fast and transparent recovery for continuous availability of cluster-based servers