Title :
Remote Restart for a High Performance Virtual Machine Recovery in a Cloud
Author :
Salapura, Valentina ; Harper, Richard
Author_Institution :
IBM T.J. Watson Res. Center, Yorktown Heights, NY, USA
Abstract :
In this paper, we present a scalable parallel virtual machine planning and fail over method that enables high availability at a VM level in a data center. The solution is implemented and used in IBM´s CMS enterprise private cloud as a high availability feature for efficient fail over in large data centers with a large number of servers, VMs, and a large number of disks. The introduced restart system enables dynamic and at-fail over-time planning and execution, and keeps the recovery time within limits of service level agreement (SLA) allowed time budget. The initial serial fail over time is reduced by a factor of up to 11 for parallel implementation, and by a factor of up to 44 for parallel fail over - parallel storage mapping implementation. As part of our future work, we plan to explore the applicability of this planning and fail over solution for Disaster Recovery.
Keywords :
business continuity; cloud computing; computer centres; contracts; parallel processing; virtual machines; IBM CMS enterprise private cloud; SLA; VM level; data center; disaster recovery; dynamic at-failover-time execution; dynamic at-failover-time planning; failover method; high-availability feature; high-performance virtual machine recovery; large-data centers; parallel failover; parallel storage mapping implementation; recovery time; remote restart system; scalable-parallel virtual machine planning; serial failover time reduction; service level agreement; Cloud computing; Computer architecture; Maintenance engineering; Monitoring; Planning; Servers; Virtual machining; Automation; Cloud Computing; Disaster Recovery; Enterprise Class; High Availability; Virtualization;
Conference_Titel :
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4673-7286-2
DOI :
10.1109/CLOUD.2015.52