CloudBruno: A Low-Overhead Online Workload Prediction Framework for Cloud Computing-Reference-Cited by-同舟云学术

CloudBruno: A Low-Overhead Online Workload Prediction Framework for Cloud Computing

Published:2022-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Cloud Engineering (IC2E)
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Author:

Jayakumar Vinodh Kumaran¹,Arbat Shivani²,Kim In Kee²,Wang Wei¹

Affiliation:

1. The University of Texas at San Antonio,Computer Science

2. University of Georgia,Computer Science

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9946295/9946237/09946321.pdf?arnumber=9946321

Reference50 articles.

1. Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters;bodik;USENIX Workshop on Hot Topics in Cloud Computing (HotCloud),2009

2. Workload Predicting-Based Automatic Scaling in Service Clouds

3. Online Self-Reconfiguration with Performance Guarantee for Energy-Efficient Large-Scale Cloud Computing Data Centers

4. Dynamic Placement of Virtual Machines for Managing SLA Violations

5. Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS

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