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Microscaler: Cost-effective Scaling for Microservice Applications in the Cloud with an Online Learning Approach

  • Published:2020 Issue: Volume: Page:1-1
  • ISSN:2168-7161
  • Container-title:IEEE Transactions on Cloud Computing
  • language:
  • Short-container-title:IEEE Trans. Cloud Comput.

Author:

Yu Guangba,Chen Pengfei,Zheng Zibin

Funder

Guangdong Introducing Innovative and Entrepreneurial Teams

National Natural Science Foundation of China

National Key R and D Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Software

Cited by 39 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. Smart HPA: A Resource-Efficient Horizontal Pod Auto-Scaler for Microservice Architectures;2024 IEEE 21st International Conference on Software Architecture (ICSA);2024-06-04

2. Performance Optimization of Web Front-End Frameworks: Automatic Adjustment Strategies Based on Bayesian Optimization Algorithm;2024 International Conference on Machine Intelligence and Digital Applications;2024-05-30

3. Evaluation of Application Layer DDoS Attack Effect in Cloud Native Applications;IEEE Transactions on Cloud Computing;2024-04

4. GeoScale: Microservice Autoscaling With Cost Budget in Geo-Distributed Edge Clouds;IEEE Transactions on Parallel and Distributed Systems;2024-04

5. Cdascaler: a cost-effective dynamic autoscaling approach for containerized microservices;Cluster Computing;2024-01-18
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