Intelligent Selection of Fault Tolerance Techniques on the Grid

• Published in: Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007) pp. 69 - 76
• Main Authors: Vanderster, D.C., Dimopoulos, N.J., Sobie, R.J.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2007
• Subjects: Checkpointing; Computational intelligence; Computational modeling; Costs; Delay; Fault tolerance; Grid computing; Processor scheduling; Resilience; Runtime
• ISBN: 9780769530642; 0769530648
• DOI: 10.1109/E-SCIENCE.2007.45

The emergence of computational grids has lead to an increased reliance on task schedulers that can guarantee the completion of tasks that are executed on unreliable systems. There are three common techniques for providing task-level fault tolerance on a grid: retrying, replicating, and checkpointing. While these techniques are varyingly successful at providing resilience to faults, each of them presents a tradeoff between performance and resource cost. As such, tasks having unique urgency requirements would ideally be placed using one of the techniques; for example, urgent tasks are likely to prefer the replication technique, which guarantees timely completion, whereas low priority tasks should not incur any extra resource cost in the name of fault tolerance. This paper introduces a placement and selection strategy which, by computing the utility of each fault tolerance technique in relation to a given task, finds the set of allocation options which optimizes the global utility. Heuristics which take into account the value offered by a user, the estimated resource cost, and the estimated response time of an option are presented. Simulation results show that the resulting allocations have improved fault tolerance, runtime, profit, and allow users to prioritize their tasks.