Predicting Scheduling Failures in the Cloud: A Case Study with Google Clusters and Hadoop on Amazon EMR
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7335977/7336120/07336144.pdf?arnumber=7336144
Cited by 17 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. Machine learning job failure analysis and prediction model for the cloud environment;High-Confidence Computing;2023-12
2. Preliminary Exploration on Node-To-Node Fault Tolerance Coordination in Distributed System;2023 IEEE International Conference on Computing (ICOCO);2023-10-09
3. Multi-agent Reinforcement Learning-based Adaptive Heterogeneous DAG Scheduling;ACM Transactions on Intelligent Systems and Technology;2023-10-03
4. Time Machine: Generative Real-Time Model for Failure (and Lead Time) Prediction in HPC Systems;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN);2023-06
5. Cloud failure prediction based on traditional machine learning and deep learning;Journal of Cloud Computing;2022-09-19
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