Cascaded Anomaly Detection with Coarse Sampling in Distributed Systems-Reference-Cited by-同舟云学术

Cascaded Anomaly Detection with Coarse Sampling in Distributed Systems

Published:2022 Issue: Volume: Page:181-200
ISSN:0302-9743
Container-title:Big-Data-Analytics in Astronomy, Science, and Engineering
language:
Short-container-title:

Author:

Bădică Amelia^ORCID,Bădică Costin^ORCID,Bolanowski Marek^ORCID,Fidanova Stefka^ORCID,Ganzha Maria^ORCID,Harizanov Stanislav^ORCID,Ivanovic Mirjana^ORCID,Lirkov Ivan^ORCID,Paprzycki Marcin^ORCID,Paszkiewicz Andrzej^ORCID,Tomczyk Kacper^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-96600-3_13

Reference32 articles.

1. Janus, P., Ganzha, M., Bicki, A., Paprzycki, M.: Applying machine learning to study infrastructure anomalies in a mid-size data center - preliminary considerations. In: Proceedings of the 54th Hawaii International Conference on System Sciences (2021). http://hdl.handle.net/10125/70636. https://doi.org/10.24251/HICSS.2021.025

2. Neu, D.A., Lahann, J., Fettke, P.: A systematic literature review on state-of-the-art deep learning methods for process prediction. Artif. Intell. Rev. (2021). https://doi.org/10.1007/s10462-021-09960-8

3. Williams, A.W., Pertet, S.M., Narasimhan, P.: Tiresias: black-box failure prediction in distributed systems. In: Proceedings of the 2007 IEEE International Parallel and Distributed Processing Symposium, Long Beach, CA, USA, pp. 1–8. IEEE (2007). https://doi.org/10.1109/IPDPS.2007.370345

4. Mariani, L., Pezzè, M., Riganelli, O., Xin, R.: Predicting failures in multi-tier distributed systems. J. Syst. Softw. 161, 110464 (2020). https://doi.org/10.1016/j.jss.2019.110464

5. Chen, X., Lu, C., Pattabiraman, K.: Failure prediction of jobs in compute clouds: a google cluster case study. In: Proceedings of the 2014 IEEE International Symposium on Software Reliability Engineering Workshops, Naples, Italy, pp. 341–346. IEEE (2014). https://doi.org/10.1109/ISSREW.2014.105