Multivariate LSTM-Based Location-Aware Workload Prediction for Edge Data Centers-Reference-Cited by-同舟云学术

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Multivariate LSTM-Based Location-Aware Workload Prediction for Edge Data Centers

Published:2019-05 Issue: Volume: Page:
ISSN:
Container-title:2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
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Author:

Nguyen Chanh,Klein Cristian,Elmroth Erik

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8746066/8752631/08752650.pdf?arnumber=8752650

Cited by 22 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. Multivariate LSTM for Execution Time Prediction in HPC for Distributed Deep Learning Training;2024 IEEE 27th International Symposium on Real-Time Distributed Computing (ISORC);2024-05-22

2. A novel workload forecasting model for cloud computing using ALAA-DBN algorithm;Multimedia Tools and Applications;2024-05-21

3. A Novel Predictive Model for Edge Computing Resource Scheduling Based on Deep Neural Network;Computer Modeling in Engineering & Sciences;2024

4. Edge Workload Prediction Based on Deep Learning;5G Edge Computing;2024

5. Intelligent and Decentralized Resource Allocation in Vehicular Edge Computing Networks;IEEE Internet of Things Magazine;2023-12

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