Heuristic Algorithms for Energy and Performance Dynamic Optimization in Cloud Computing

Authors

  • Lizheng Guo Department of Computer Science and Engineering, Henan University of Urban Construction, Pindingshan 467036 & College of Information Sciences and Technology, Donghua University, Shanghai 201620
  • Yifei Zhang Department of Computer Science and Engineering, Henan University of Urban Construction, Pindingshan 467036
  • Shuguang Zhao College of Information Sciences and Technology Donghua University, Shanghai 201620

Keywords:

Cloud computing, green computing, virtual machine, dynamic consolidation

Abstract

Cloud computing becomes increasingly popular for hosting all kinds of applications not only due to their ability to support dynamic provisioning of virtualized resources to handle workload fluctuations but also because of the usage based on pricing. This results in the adoption of data centers which store, process and present the data in a seamless, efficient and easy way. Furthermore, it also consumes an enormous amount of electrical energy, then leads to high using cost and carbon dioxide emission. Therefore, we need a Green computing solution that can not only minimize the using costs and reduce the environment impact but also improve the performance. Dynamic consolidation of Virtual Machines (VMs), using live migration of the VMs and switching idle servers to sleep mode or shutdown, optimizes the energy consumption. We propose an adaptive underloading detection method of hosts, VMs migration selecting method and heuristic algorithm for dynamic consolidation of VMs based on the analysis of the historical data. Through extensive simulation based on random data and real workload data, we show that our method and algorithm observably reduce energy consumption and allow the system to meet the Service Level Agreements (SLAs).

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Author Biographies

Lizheng Guo, Department of Computer Science and Engineering, Henan University of Urban Construction, Pindingshan 467036 & College of Information Sciences and Technology, Donghua University, Shanghai 201620

Lizheng Guo has completed his Maser’s degrees in the College of Computer Science and Technology of Chongqing University of Posts and Telecommunications, Chongqing, China in 2005. He is currently pursuing his Ph.D. in Pattern Recognition and Intelligent System at the College of Information Science and Technology, Donghua University, Shanghai, China. His research interests include distributed system, intelligent computing, cloud computing and grid computing.

Yifei Zhang, Department of Computer Science and Engineering, Henan University of Urban Construction, Pindingshan 467036

Yifei Zhang is a lecture at the Department of Computer Science, Henan University of Urban Construction (since 2009).His main interests focus on computer networks and operating systems.

Shuguang Zhao, College of Information Sciences and Technology Donghua University, Shanghai 201620

Shuguang Zhao received the B.S. degree in information processing from Xidian University, Xi’an, China, 1986, the M.S. degree in signal and information processing and Ph.D. degree in circuit and system from Xidian University, Xi’an, China, in 1992 and 2003, respectively. He is currently Professor at Donghua University. His research interests include evolvable hardware and intelligent signal processing.

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Published

2018-02-09

How to Cite

Guo, L., Zhang, Y., & Zhao, S. (2018). Heuristic Algorithms for Energy and Performance Dynamic Optimization in Cloud Computing. Computing and Informatics, 36(6), 1335–1360. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/2017_6_1335

Issue

Vol. 36 No. 6 (2017): Computing and Informatics

Section

Articles