We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Efficient Deployment of Main-Memory DBMS in Virtualized Data Centers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Seibold, M. ; Dept. of Comput. Sci., Tech. Univ. Munchen, Garching, Germany ; Wolke, A. ; Albutiu, M. ; Bichler, M.
more authors

Running emerging main-memory database systems within virtual machines causes huge overhead, because these systems are highly optimized to get the most out of bare metal servers. But running these systems on bare metal servers results in low resource utilization, because database servers often have to be sized for peak loads, much higher than the average load. Instead, we propose to deploy them within light-weight containers that allow to control resource usage and to make use of spare resources by temporarily running other applications on the database server using virtual machines (VMs). The servers on which these VMs would normally run can be suspended, to save energy costs. But current database systems do not handle dynamic changes to resource allocation well and accurate estimates on resource demand are required to maintain SLAs. We focus on emerging main-memory database systems that support the mixed workloads of today's business intelligence applications and propose an cooperative approach in which the DBMS communicates its resource demand, gets informed about currently assigned resources and adapts its resource usage accordingly. We analyze the performance impact on the database system when spare resources are used by VMs and monitor SLA compliance.

Published in:

Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on

Date of Conference:

24-29 June 2012