EMPIRICAL STUDY ON OFFLINE VS LIVE MIGRATION

Virtualization is a state-of-the-art technology facilitating resource optimizations by providing an environment conducive to execute as many VMs as possible. The proliferation of VMs on a physical server makes the resource management convoluted. This difficulty in managing the resources results in these VMs not to perform optimally and seldom demonstrate poor performance. Often this underperformance may result in the VM to fail and stop working. Hence, it becomes necessary to migrate a VM from a source to a destination. When the migration decision has been taken, it becomes necessary to analyze the performance of applications during migration since all the applications will not exhibit the same performance during migration. The Migration can be conducted offline or live. This paper aims at analyzing the performance of offline and live migration techniques with respect to total migration time, downtime and performance of an application during migration.

[1]  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.

[2]  Narayan A. Joshi.  LOAD BALANCING IN CLOUD USING PROCESS MIGRATION , 2014 .

[3]  Saneyasu Yamaguchi,et al.  A Study on Performance of Processes in Migrating Virtual Machines , 2011, 2011 Tenth International Symposium on Autonomous Decentralized Systems.

[4]  Hai Jin,et al.  Live virtual machine migration with adaptive, memory compression , 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

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

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

[7]  Mohamed Cheriet,et al.  Decreasing live virtual machine migration down-time using a memory page selection based on memory change PDF , 2010, 2010 International Conference on Networking, Sensing and Control (ICNSC).

[8]  Khaled Z. Ibrahim,et al.  Optimized pre-copy live migration for memory intensive applications , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[9]  Hanan Lutfiyya,et al.  Replication and Migration as Resource Management Mechanisms for Virtualized Environments , 2010, 2010 Sixth International Conference on Autonomic and Autonomous Systems.

[10]  Feng Liu,et al.  Live virtual machine migration based on improved pre-copy approach , 2010, 2010 IEEE International Conference on Software Engineering and Service Sciences.

[11]  Hai Jin,et al.  Performance and energy modeling for live migration of virtual machines , 2011, HPDC.

[12]  Abhishek Chandra,et al.  Starling: Minimizing Communication Overhead in Virtualized Computing Platforms Using Decentralized Affinity-Aware Migration , 2010, 2010 39th International Conference on Parallel Processing.

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

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

[15]  Xiaohong Jiang,et al.  Live Migration of Multiple Virtual Machines with Resource Reservation in Cloud Computing Environments , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[16]  Fan Ying,et al.  A new live virtual machine migration strategy , 2012, 2012 International Symposium on Information Technologies in Medicine and Education.