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Enabling Scalable Cloud Infrastructure Using Autonomous VM Migration.

Authors :
Choi, Hyung Won
Sohn, Andrew
Kwak, Hukeun
Chung, Kyusik
Source :
2012 IEEE 14th International Conference on High Performance Computing & Communication & 2012 IEEE 9th International Conference on Embedded Software & Systems; 1/ 1/2012, p1066-1073, 8p
Publication Year :
2012

Abstract

Service providers and enterprises capitalize on evolving cloud computing technologies when building datacenters for their own computing infrastructure and/or for providing services to others. Virtual machines and their migration are an important underlying technology of Infrastructure as a Service (IaaS) for building efficient cloud computing infrastructure on a cluster of servers. Autonomous migration of virtual machines is designed to increase the overall resource utilization on a cluster of servers. If a particular computing pattern caused imbalance that triggers migration, this pattern will be remembered or "learned" with its corresponding migration details for future use. In this paper, we use a proactive learning methodology that not only accumulates the past history of computing patterns and resulting migration decisions but more importantly searches all predefined possibilities for the most suitable decisions. We set up an experimental environment that consists of extensive real world benchmarking problems and a cluster of 16 physical machines each of which has on average eight virtual machines. We demonstrate through experimental results that our self regulated autonomous VM migration increases resource utilization of the servers on which cloud computing IaaS is currently running. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781467321648
Database :
Complementary Index
Journal :
2012 IEEE 14th International Conference on High Performance Computing & Communication & 2012 IEEE 9th International Conference on Embedded Software & Systems
Publication Type :
Conference
Accession number :
86825916
Full Text :
https://doi.org/10.1109/HPCC.2012.156