Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CLOUD.2012.13
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.
Servers, Resource management, Linux, Database systems, Virtual machining, Time factors, Main-memory DBMS, Cloud Computing, Infrastructure-As-A-Service
Michael Seibold, Andreas Wolke, Martina Albutiu, Martin Bichler, Alfons Kemper, Thomas Setzer, "Efficient Deployment of Main-Memory DBMS in Virtualized Data Centers", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 311-318, doi:10.1109/CLOUD.2012.13