Using MIMO linear control for load balancing in computing systems

Abstract

Load balancing is widely used in computing systems as a way to optimize performance by equalizing loads to reduce delays, such as adjusting the size of memory pools to balance resource demands in a database management system. Load balancing is generally approached as a nonlinear constrained optimization in which dynamics are ignored. We approach load balancing differently - as a feedback controller design problem using a multiple input multiple output linear quadratic regulator (LQR) that achieves the constrained optimization objective. Such an approach allows us to exploit well established techniques for handling disturbances (e.g., due to changes in workloads) and to incorporate the cost of control (e.g., throughput reductions due to resizing buffer pools) by properly selecting the LQR Q and R matrices. From studies of DB2 Universal Database Server using industry standard benchmarks, we show that the controller obtains a factor of three increase in throughput for an OLTP workload and a 59% reduction in response times for a DSS workload.