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As grids typically consist of autonomously managed subsystems with strongly varying resources, fault-tolerance forms an important aspect of the scheduling process of applications. Two well-known techniques for providing fault-tolerance in grids are periodic task checkpointing and replication. Both techniques mitigate the amount of work lost due to changing system availability but can introduce significant run-time overhead. The latter largely depends on the length of checkpointing interval and the chosen number of replicas, respectively. This paper presents a dynamic scheduling algorithm that switches between periodic checkpointing and replication to exploit the advantages of both techniques and to reduce the overhead. Furthermore, several novel heuristics are discussed that perform on-line adaptive tuning of the checkpointing period based on historical information on resource behavior. Simulation-based comparison of the proposed combined algorithm versus traditional strategies based on checkpointing and replication only, suggests significant reduction of average task makespan for systems with varying load.

Providing Fault-Tolerance in Unreliable Grid Systems Through Adaptive Checkpointing and Replication