The use of economic models to capture importance policy for autonomic database management systems

Authors:
Patrick Martin;Mingyi Zhang;Wendy Powley;Harley Boughton;Paul Bird;Randy Horman
Affiliations:
Queen's University, Kingston, ON, Canada;Queen's University, Kingston, ON, Canada;Queen's University, Kingston, ON, Canada;IBM Toronto Lab, Markham, ON, Canada;IBM Toronto Lab, Markham, ON, Canada;IBM Toronto Lab, Markham, ON, Canada
Venue:
Proceedings of the 1st ACM/IEEE workshop on Autonomic computing in economics
Year:
2011

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Abstract

A key advantage of Autonomic Database Management Systems will be their ability to manage according to business policies. Translating high-level business policies into low-level tuning actions and parameters is, however, a non-trivial problem as there is little similarity in the metrics used for measuring database performance and business performance. These translations can be simplified, however, by having a model that reflects the business policies. In this paper, we utilize an economic model to implement importance policy as a parameter for the allocation of system resources. The relative importance of the workloads can therefore be utilized in allocating system resources. We simulate the model in order to demonstrate the effectiveness of the approach. We present experiments to show the impact of the relative importance of workloads on the allocation of resources, specifically main memory for buffer space and CPU.