Enabling scalable cloud infrastructure using autonomous VM migration
Document Type
Conference Proceeding
Publication Date
12-7-2012
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. © 2012 IEEE.
Identifier
84870400029 (Scopus)
ISBN
[9780769547497]
Publication Title
Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications Hpcc 2012 9th IEEE International Conference on Embedded Software and Systems Icess 2012
External Full Text Location
https://doi.org/10.1109/HPCC.2012.156
First Page
1066
Last Page
1073
Recommended Citation
Choi, Hyung Won; Sohn, Andrew; Kwak, Hukeun; and Chung, Kyusik, "Enabling scalable cloud infrastructure using autonomous VM migration" (2012). Faculty Publications. 17876.
https://digitalcommons.njit.edu/fac_pubs/17876
