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SPSRG: a prediction approach for correlated failures in distributed computing systems

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Abstract

Failure instances in distributed computing systems (DCSs) have exhibited temporal and spatial correlations, where a single failure instance can trigger a set of failure instances simultaneously or successively within a short time interval. In this work, we propose a correlated failure prediction approach (CFPA) to predict correlated failures of computing elements in DCSs. The approach models correlated-failure patterns using the concept of probabilistic shared risk groups and makes a prediction for correlated failures by exploiting an association rule mining approach in a parallel way. We conduct extensive experiments to evaluate the feasibility and effectiveness of CFPA using both failure traces from Los Alamos National Lab and simulated datasets. The experimental results show that the proposed approach outperforms other approaches in both the failure prediction performance and the execution time, and can potentially provide better prediction performance in a larger system.

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Notes

  1. The operator “\(\backslash \)” denotes set minus as in “\( X \backslash Y\)”, which means ‘ Y is excluded from X’.

  2. Each \(I_{k}\) corresponds to a certain CE in a DCS.

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Acknowledgments

The author would like to thank the anonymous reviewers for their invaluable suggestions which have been incorporated to improve the quality of the paper. This work was supported by the National Natural Science Foundation of China (No.61372108).

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

    Weiwei Zheng, Zhili Wang, Haoqiu Huang, Luoming Meng & Xuesong Qiu

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  1. Weiwei Zheng
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  2. Zhili Wang
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  3. Haoqiu Huang
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Correspondence to Weiwei Zheng.

Appendix : Notations

Appendix : Notations

Table 6 summarizes the notations we used.

Table 6 Summary of notation used throughout this paper
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Zheng, W., Wang, Z., Huang, H. et al. SPSRG: a prediction approach for correlated failures in distributed computing systems. Cluster Comput 19, 1703–1721 (2016). https://doi.org/10.1007/s10586-016-0633-2

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  • DOI: https://doi.org/10.1007/s10586-016-0633-2

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