Virtual machine migration for back-end mashup application deployed on OpenStack environment

Cloud computing provides a computing platform for the users to meet their demands in an efficient way. Virtualization technologies are used in the clouds to aid the efficient usage of hardware. Virtual machines are utilized to satisfy the user needs and are placed on physical machines of the cloud for effective usage of hardware resources and electricity. Optimizing the number of physical machines used helps in cutting down the power consumption by substantial amount. An optimal technique is to map virtual machines to physical machines such that the number of required physical machines is minimized. The Virtual Machine Placement problem with the target of minimizing the total energy consumption by running physical machines is an indication of increasing resource utilization and reducing cost of a data center. Virtual Machine Migration is another approach to minimize the total energy consumption and to increase resource utilization. Due to the multiple dimensionality of physical resources, there always exists a waste of resources, which results from the imbalanced use of multi-dimensional resources. Migration support can balance the utilization of multi-dimensional resources, reduce the number of running physical machines and thus lower the energy consumption. In this paper, we present a platform to test different Virtual Machine Placement and Virtual Machine Migration algorithms on real time scenarios (Cloud) and enable them to conduct different experiments. For this purpose, OpenStack private cloud is suggested as private cloud environment and OpenStack Neat is used to provide dynamic Virtual Machine Migration. Here, we have integrated OpenStack Neat with OpenStack Cloud and shown the experiment of dynamic Virtual Machine Migration in real time.

[1]  N SenthilNathan,et al.  Performance Modeling of Virtual Machine Live Migration , 2015 .

[2]  Andy Hopper,et al.  Predicting the Performance of Virtual Machine Migration , 2010, 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.

[3]  H. Shahul Hamead,et al.  Energy aware cloud service provisioning approach for green computing environment , 2013, 2013 International Conference on Energy Efficient Technologies for Sustainability.

[4]  Robert Richards,et al.  Representational State Transfer (REST) , 2006 .

[5]  Rajkumar Buyya,et al.  OpenStack Neat: a framework for dynamic and energy‐efficient consolidation of virtual machines in OpenStack clouds , 2015, Concurr. Comput. Pract. Exp..

[6]  Rajkumar Buyya,et al.  Cost of Virtual Machine Live Migration in Clouds: A Performance Evaluation , 2009, CloudCom.

[7]  Shrisha Rao,et al.  CloudSpider: Combining Replication with Scheduling for Optimizing Live Migration of Virtual Machines across Wide Area Networks , 2011, 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[8]  Yasusi Kanada,et al.  A “network-paging” based method for wide-area live-migration of VMs , 2011, The International Conference on Information Networking 2011 (ICOIN2011).

[9]  Ming Zhao,et al.  Performance Modeling of Virtual Machine Live Migration , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[10]  Umesh Deshpande,et al.  Post-copy live migration of virtual machines , 2009, OPSR.

[11]  E. S. Pilli,et al.  Live virtual machine migration techniques: Survey and research challenges , 2013, 2013 3rd IEEE International Advance Computing Conference (IACC).

[12]  Benoit Hudzia,et al.  Improving the live migration process of large enterprise applications , 2009, VTDC '09.