KAE-Informer: A Knowledge Auto-Embedding Informer for Forecasting Long-Term Workloads of Microservices

Author:

Hua Qin1ORCID,Yang Dingyu2ORCID,Qian Shiyou1ORCID,Hu Hanwen1ORCID,Cao Jian1ORCID,Xue Guangtao1ORCID

Affiliation:

1. Shanghai Jiao Tong University, China

2. Alibaba Group, China

Funder

Alibaba Group through Alibaba Innovative Research Program and Alibaba Research Intern Program

the Artificial Intelligence Technology Support Project of the Science and Technology Commission of Shanghai Municipality

the Program of Technology Innovation of the Science and Technology Commission of Shanghai Municipality

Publisher

ACM

Reference46 articles.

1. Burst-Aware Predictive Autoscaling for Containerized Microservices

2. A Review of Dynamic Resource Management in Cloud Computing;Aldossary Mohammad;Environments.Comput. Syst. Sci. Eng.,2021

3. A review of data-driven building energy consumption prediction studies

4. Shaojie Bai J. Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. https://doi.org/10.48550/ARXIV.1803.01271 10.48550/ARXIV.1803.01271

5. Shaojie Bai J. Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. https://doi.org/10.48550/ARXIV.1803.01271

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