NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms-Reference-Cited by-同舟云学术

NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms

Author:

Luo Chuan¹,Zhao Pu¹,Qiao Bo¹,Wu Youjiang²,Zhang Hongyu³,Wu Wei⁴,Lu Weihai¹,Dang Yingnong²,Rajmohan Saravanakumar⁵,Lin Qingwei¹,Zhang Dongmei¹

Affiliation:

1. Microsoft Research, China

2. Microsoft Azure, USA

3. The University of Newcastle, Australia

4. Leibniz University Hannover, Germany

5. Microsoft Office, USA

Publisher

ACM

Link

Reference49 articles.

Cited by 13 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. KnowLog: Knowledge Enhanced Pre-trained Language Model for Log Understanding;Proceedings of the 46th IEEE/ACM International Conference on Software Engineering;2024-02-06

2. CODEC: Cost-Effective Duration Prediction System for Deadline Scheduling in the Cloud;2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE);2023-10-09

3. A Failure Prediction Approach Based on BiLSTM and Deep Feature Extractor for Hard Disk Drives;2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE);2023-09-23

4. Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion;2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE);2023-09-11

5. 一个针对多种问题的磁盘故障预测模型;Frontiers of Information Technology & Electronic Engineering;2023-07