Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds

Peiyun Zhang, Sheng Shu, Mengchu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fault detection is a crucial technology to improve the performance of cloud systems. Its fixed detection cycle tends to be problematic since it faces high overhead if a small detection cycle is used for well-performing services; while risks missing many faults if a large cycle is adopted for some poorly-performing services. To solve such problems, an algorithm for adaptively adjusting dynamic detection cycle is proposed to decrease the overhead and increase fault detection performance in a cloud environment. It shortens a detection cycle for cloud systems with large fault probability, thus boosting fault detection performance. Otherwise, it increases it, thus decreasing the overhead. The algorithm is based on the proposed detection model by using a decision tree and support vector machine to increase detection performance. Experimental results show that the method is feasible and effective in comparison with some representative methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4047-4052
Number of pages6
ISBN (Electronic)9781538666500
DOIs
StatePublished - Jan 16 2019
Event2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan
Duration: Oct 7 2018Oct 10 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Conference

Conference2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
CountryJapan
CityMiyazaki
Period10/7/1810/10/18

Fingerprint

Fault detection
Decision trees
Support vector machines

Cite this

Zhang, P., Shu, S., & Zhou, M. (2019). Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 4047-4052). [8616683] (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2018.00686
Zhang, Peiyun ; Shu, Sheng ; Zhou, Mengchu. / Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds. Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 4047-4052 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).
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Zhang, P, Shu, S & Zhou, M 2019, Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds. in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 8616683, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 4047-4052, 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, 10/7/18. https://doi.org/10.1109/SMC.2018.00686

Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds. / Zhang, Peiyun; Shu, Sheng; Zhou, Mengchu.

Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4047-4052 8616683 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Zhang P, Shu S, Zhou M. Adaptively Adjusting Dynamic Detection Cycle for Fault Detection in Clouds. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4047-4052. 8616683. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). https://doi.org/10.1109/SMC.2018.00686