Measuring lead times for failure prediction-Reference-Cited by-同舟云学术

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Measuring lead times for failure prediction

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 26th Pacific Rim International Symposium on Dependable Computing (PRDC)
language:
Short-container-title:

Author:

Cerveira Frederico,Domingos Jomar,Barbosa Raul,Madeira Henrique

Funder

FCT

European Social Fund

H2020

ECSEL Joint Undertaking (JU)

Horizon 2020

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9667542/9667667/09667686.pdf?arnumber=9667686

Reference13 articles.

1. Using Hidden Semi-Markov Models for Effective Online Failure Prediction

2. Exploratory Study of Machine Learning Techniques for Supporting Failure Prediction

3. Towards Assessing Representativeness of Fault Injection-Generated Failure Data for Online Failure Prediction

4. On Configuring a Testbed for Dependability Experiments: Guidelines and Fault Injection Case Study

5. Adaptive Failure Prediction for Computer Systems: A Framework and a Case Study

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fault injection acceleration using failure models on a virtualized fault-tolerant system;2024 19th European Dependable Computing Conference (EDCC);2024-04-08

2. Lead Time Analysis for UAVs’ Failure Prediction in U-space;2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC);2023-10-24

3. Predicting Cloud Applications Failures from Infrastructure Level Data;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W);2023-06

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