TempoScale: A Cloud Workloads Prediction Approach Integrating Short-Term and Long-Term Information

Author:

Wen Linfeng1,Xu Minxian1,Toosi Adel N.2,Ye Kejiang1

Affiliation:

1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,China

2. Monash University,Faculty of Information Technology,Australia

Publisher

IEEE

Reference29 articles.

1. Elasticity in cloud computing: State of the art and research challenges;AI-Dhuraibi,2018

2. Kubernetes and the path to cloud native;Brewer,2015

3. Deep reinforcement learning in cloud elasticity through offline learning and return based scaling;Chrysopoulos

4. Host load prediction in cloud computing with discrete wavelet transformation (dwt) and bidirectional gated recurrent unit (bigru) network;Dogani,2023

5. A framework for characterizing very large cloud workload traces with unsupervised learning;Suleiman

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