Virtual machine management system based on the power saving algorithm in cloud

This work uses the open source codes and PHP web programming to implement a resource management system with power saving method for virtual machines. We propose a system integrated with open source software, such as KVM and Libvirt, to construct a virtual cloud management platform. This system can detect the status of cloud resources via SNMP, calculate the operation efficiency of the overall system, allocate virtual machines through the live migration technology, and turn off extra machines in the cloud to save energy. According to our proposed power saving method, we have constructed a power efficient virtualization management platform in the cloud. Our objective is to provide enterprises or end users with power saving private cloud solutions. In this work we have also built a web page to allow users to easily access and control the cloud virtualization resources, i.e., users can manage virtual machines and monitor the status of resources via the web interface. From analysis of the experimental results of live migration of virtual machines, this work demonstrates that efficient use of hardware resources is realized by the power saving method, and the aim of power saving for cloud computing is achieved.

[1]  Jun Wang,et al.  Power Control by Distribution Tree with Classified Power Capping in Cloud Computing , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[2]  Ching-Chi Lin,et al.  Energy-Aware Virtual Machine Dynamic Provision and Scheduling for Cloud Computing , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[3]  Eric Jul,et al.  Self-migration of operating systems , 2004, EW 11.

[4]  T YangLaurence,et al.  Green computing and communications , 2013 .

[5]  Chao-Tung Yang,et al.  A Dynamic Resource Allocation Model for Virtual Machine Management on Cloud , 2011, FGIT-GDC.

[6]  Rajkumar Buyya,et al.  Energy Efficient Resource Management in Virtualized Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[7]  Qiang Huang,et al.  Power Consumption of Virtual Machine Live Migration in Clouds , 2011, 2011 Third International Conference on Communications and Mobile Computing.

[8]  Glauco Estácio Gonçalves,et al.  A Survey on Open-source Cloud Computing Solutions , 2010 .

[9]  Karsten Schwan,et al.  High performance and scalable I/O virtualization via self-virtualized devices , 2007, HPDC '07.

[10]  Gil Neiger,et al.  Intel virtualization technology , 2005, Computer.

[11]  Rodney S. Tucker,et al.  Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport , 2011, Proceedings of the IEEE.

[12]  Ruay-Shiung Chang,et al.  Green virtual networks for cloud computing , 2010, 2010 5th International ICST Conference on Communications and Networking in China.

[13]  Lizhe Wang,et al.  Resource management of distributed virtual machines , 2012, Int. J. Ad Hoc Ubiquitous Comput..

[14]  Rajiv Ranjan,et al.  Cloud monitoring for optimizing the QoS of hosted applications , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[15]  Richard Wolski,et al.  The Eucalyptus Open-Source Cloud-Computing System , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.

[16]  Feng Zhao,et al.  Energy aware consolidation for cloud computing , 2008, CLUSTER 2008.

[17]  Euiseong Seo,et al.  Energy-Based Accounting and Scheduling of Virtual Machines in a Cloud System , 2011, 2011 IEEE/ACM International Conference on Green Computing and Communications.

[18]  Andrew Warfield,et al.  Live migration of virtual machines , 2005, NSDI.

[19]  Tal Garfinkel,et al.  Virtual machine monitors: current technology and future trends , 2005, Computer.

[20]  Jun Wang,et al.  Classified power capping by network distribution trees for green computing , 2013, Cluster Computing.

[21]  A. Kivity,et al.  kvm : the Linux Virtual Machine Monitor , 2007 .

[22]  Euiseong Seo,et al.  Energy-credit scheduler: An energy-aware virtual machine scheduler for cloud systems , 2014, Future Gener. Comput. Syst..

[23]  Borja Sotomayor,et al.  Virtual Infrastructure Management in Private and Hybrid Clouds , 2009, IEEE Internet Computing.

[24]  Xuejie Zhang,et al.  An Approach to Optimized Resource Scheduling Algorithm for Open-Source Cloud Systems , 2010, 2010 Fifth Annual ChinaGrid Conference.

[25]  B. Gayathri,et al.  Green cloud computing , 2012 .

[26]  Albert Y. Zomaya,et al.  Energy efficient utilization of resources in cloud computing systems , 2010, The Journal of Supercomputing.

[27]  Dejan S. Milojicic,et al.  Process migration , 1999, ACM Comput. Surv..

[28]  Chao-Tung Yang,et al.  A Virtualized HPC Cluster Computing Environment on Xen with Web-Based User Interface , 2009, HPCA.

[29]  Lizhe Wang,et al.  Review of performance metrics for green data centers: a taxonomy study , 2011, The Journal of Supercomputing.

[30]  Juan Li,et al.  An overview of energy efficiency techniques in cluster computing systems , 2013, Cluster Computing.

[31]  Ole Agesen,et al.  A comparison of software and hardware techniques for x86 virtualization , 2006, ASPLOS XII.

[32]  Alan L. Cox,et al.  Concurrent Direct Network Access for Virtual Machine Monitors , 2007, 2007 IEEE 13th International Symposium on High Performance Computer Architecture.

[33]  Rafael Moreno-Vozmediano,et al.  Elastic management of cluster-based services in the cloud , 2009, ACDC '09.

[34]  Yaozu Dong.  Extending Xen* with IntelŴVirtualization Technology , 2006 .

[35]  M. Savoie,et al.  Converged Optical Network Infrastructures in Support of Future Internet and Grid Services Using IaaS to Reduce GHG Emissions , 2009, Journal of Lightwave Technology.

[36]  Feng Xia,et al.  Green computing and communications , 2011, The Journal of Supercomputing.

[37]  WangLizhe,et al.  Review of performance metrics for green data centers , 2013 .

[38]  Jian Wang,et al.  Towards enabling Cyberinfrastructure as a Service in Clouds , 2013, Comput. Electr. Eng..

[39]  Andrew Warfield,et al.  Xen and the art of virtualization , 2003, SOSP '03.

[40]  Kazuhiko Kato,et al.  Power-Saving in Large-Scale Storage Systems with Data Migration , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[41]  Ching-Chi Lin,et al.  Energy-efficient Virtual Machine Provision Algorithms for Cloud Systems , 2011, 2011 Fourth IEEE International Conference on Utility and Cloud Computing.

[42]  Jan Weglarz,et al.  Practical power consumption estimation for real life HPC applications , 2013, Future Gener. Comput. Syst..

[43]  Douglas Thain,et al.  A Comparison and Critique of Eucalyptus, OpenNebula and Nimbus , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[44]  Minoru Uehara,et al.  A Study on Constructing an Energy Saving Cloud System Powered by Photovoltaic Generation , 2012, 2012 15th International Conference on Network-Based Information Systems.

[45]  Marianne Shaw,et al.  Rethinking the design of virtual machine monitors , 2005, Computer.

[46]  P. K. Banerjee,et al.  Method to Fairly Distribute Power Saving Benefits in a Cloud among Various Customers , 2012, 2012 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM).

[47]  Cong Li,et al.  Kernel-based Virtual Machine , 2017 .

[48]  Yi Zhao,et al.  Adaptive Distributed Load Balancing Algorithm Based on Live Migration of Virtual Machines in Cloud , 2009, 2009 Fifth International Joint Conference on INC, IMS and IDC.

[49]  Xiaoli Li,et al.  Towards energy-efficient parallel analysis of neural signals , 2011, Cluster Computing.

[50]  Yaozu Dong,et al.  Optimizing Xen VMM Based on Intel® Virtualization Technology , 2008, 2008 International Conference on Internet Computing in Science and Engineering.

[51]  Chao-Tung Yang,et al.  Implementation of a Power Saving Method for Virtual Machine Management in Cloud , 2013, 2013 International Conference on Cloud Computing and Big Data.

[52]  Antonio Corradi,et al.  Increasing Cloud power efficiency through consolidation techniques , 2011, 2011 IEEE Symposium on Computers and Communications (ISCC).

[53]  RosenblumMendel,et al.  Virtual Machine Monitors , 2005 .