@inproceedings{3a4856c80a0142a9bb446a0daeeacb9a,
title = "Optimization of cloud task processing with checkpoint-restart mechanism",
abstract = "In this paper, we aim at optimizing fault-tolerance techniques based on a checkpointing/restart mechanism, in the context of cloud computing. Our contribution is three-fold. (1) We derive a fresh formula to compute the optimal number of checkpoints for cloud jobs with varied distributions of failure events. Our analysis is not only generic with no assumption on failure probability distribution, but also attractively simple to apply in practice. (2) We design an adaptive algorithm to optimize the impact of checkpointing regarding various costs like checkpointing/restart overhead. (3) We evaluate our optimized solution in a real cluster environment with hundreds of virtual machines and Berkeley Lab Checkpoint/Restart tool. Task failure events are emulated via a production trace produced on a large-scale Google data center. Experiments confirm that our solution is fairly suitable for Google systems. Our optimized formula outperforms Young's formula by 3-10 percent, reducing wallclock lengths by 50-100 seconds per job on average.",
keywords = "BLCR, Checkpoint-Restart Mechanism, Cloud Computing, Google, Optimal Checkpointing Interval",
author = "Sheng Di and Yves Robert and Fr{\'e}d{\'e}ric Vivien and Derrick Kondo and Wang, {Cho Li} and Franck Cappello",
year = "2013",
doi = "10.1145/2503210.2503217",
language = "English (US)",
isbn = "9781450323789",
series = "International Conference for High Performance Computing, Networking, Storage and Analysis, SC",
publisher = "IEEE Computer Society",
booktitle = "Proceedings of SC 2013",
note = "2013 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013 ; Conference date: 17-11-2013 Through 22-11-2013",
}