Autonomic performance management of cloud server based on adaptive control method
文献类型：会议论文
| 作者 | Shi, Xiaoyu1 ; Shang, Ming-Sheng1; Tian, Wenhong1; Khushnood, Abbas1; Wang, Shuai2; Wu, Tianshu3
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| 出版日期 | 2018 |
| 会议日期 | March 27, 2018 - March 29, 2018 |
| 会议地点 | Zhuhai, China |
| DOI | 10.1109/ICNSC.2018.8361345 |
| 页码 | 1-6 |
| 英文摘要 | Cloud computing provides a promising approach for efficiently managing the performance of servers via advanced resource management, hence it becomes one of the important hotspots in high-performance computing field recently. For the existing performance management solutions of cloud servers, they always show inefficiency issues when dealing with the dynamic and burst web workloads. In this paper, we propose an autonomic performance management of cloud servers, which adopt the linear quadratic Gaussian with stochastic method (LQGwS). In the face of dynamic and burst web workloads, it guarantees the workload balance between different Web applications by adaptively adjusting the amount of resource allocation to each virtual machine. Furthermore, in order to deal with the unknown disturbances in the Web system, the LQGwS describes the Web system as a coupled multiple-input-multiple-output system and uses the Autoregressive moving-average model with exogenous inputs model (ARMAX) firstly, and then constructs the optimal resource allocation scheme based on minimizing an average cost function among a set of models, which are generated according to a Gauss distribution. Through the test of real network load, the results of this experiment on the XEN-based platform show that the proposed control strategy has better performance than existing solutions under dynamical workloads in terms of control accuracy and stability. © 2018 IEEE. |
| 会议录 | 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018
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| 语种 | 英语 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/7952]  |
| 专题 | 大数据挖掘及应用中心 |
| 作者单位 | 1.Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, China; 2.China West Normal University, Nanchong, Sichuan, China; 3.Chongqing University, Chongqing, China |
| 推荐引用方式 GB/T 7714 | Shi, Xiaoyu,Shang, Ming-Sheng,Tian, Wenhong,et al. Autonomic performance management of cloud server based on adaptive control method[C]. 见:. Zhuhai, China. March 27, 2018 - March 29, 2018. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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