A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment

A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment

Abstract Server workload in the form of cloud-end clusters is a key factor in server maintenance and task scheduling. How to balance and optimize hardware resources and computation resources should thus receive more attention. However, we have observed that the disordered execution of running applic...

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Bibliographic Details
Main Authors: Yonghua Zhu, Weilin Zhang, Yihai Chen, Honghao Gao
Format: Article
Language:English
Published: SpringerOpen 2019-12-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Workload prediction
LSTM
Encoder-Decoder Network
Attention mechanism
Cloud environment
Online Access:https://doi.org/10.1186/s13638-019-1605-z

Internet

https://doi.org/10.1186/s13638-019-1605-z

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