Prediction and Adaptation in Active Harmony
I-Hsin Chung and J.K. Hollingsworth
HPDC (to appear July 2004)
Active Harmony provides a way to automate performance tuning. In this
paper, we apply the Active Harmony system to improve the performance of
a cluster-based web service system. The performance improvement cannot
easily be achieved by tuning individual components for such a system. The
experimental results show that there is no single configuration for
the system that performs well for all kinds of workloads. By tuning the
parameters, Active Harmony helps the system adapt to different workloads
and improve the performance up to 16%. For scalability, we demonstrate
how to reduce the time when tuning a large system with many tunable
parameters. Finally an algorithm is proposed to automatically adjust
the structure of cluster-based web systems, and the system throughput
is improved up to 70% using this technique.