Thoth: Automatic Resource Management with Machine Learning for Container-based Cloud Platform

被引:15
作者
Sangpetch, Akkarit [1 ]
Sangpetch, Orathai [1 ]
Juangmarisakul, Nut [1 ]
Warodom, Supakorn [1 ]
机构
[1] King Mongkuts Inst Technol Ladkrabang, Fac Engn, Dept Comp Engn, 1 Chalongkrung Rd, Bangkok, Thailand
来源
CLOSER: PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE | 2017年
关键词
Cloud Computing; Scheduling; Container; Platform-as-a-Service;
D O I
10.5220/0006254601030111
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Platform-as-a-Service (PaaS) providers often encounter fluctuation in computing resource usage due to workload changes, resulting in performance degradation. To maintain acceptable service quality, providers may need to manually adjust resource allocation according to workload dynamics. Unfortunately, this approach will not scale well as the number of applications grows. We thus propose Thoth, a dynamic resource management system for PaaS using Docker container technology. Thoth automatically monitors resource usage and dynamically adjusts appropriate amount of resources for each application. To implement the automatic-scaling algorithm, we select three algorithms, namely Neural Network, Q-Learning and our rule-based algorithm, to study and evaluate. The experimental results suggest that Q-Learning can the best adapt to the load changes, followed by a rule-based algorithm and NN. With Q-Learning, Thoth can save computing resources by 28.95% and 21.92%, compared to Neural Network and the rule-based algorithm respectively, without compromising service quality.
引用
收藏
页码:75 / 83
页数:9
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