Mining the Performance of Complex Systems

• Venue: ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
• Year: 1999

The enormous amount of data that can be collected in any performance evaluation study of a complex system indicates the need for methodologies and systems capable of analyzing, fusing, and reducing high-dimensional data spaces with very high speed. In this paper we devise and present an adaptation of the Knowledge Discovery in Databases (KDD) framework that supports the above functionality for performance data of complex software/hardware system pairs. The KDD framework considered integrates database technology along with data mining techniques for uncovering patterns from performance data and static system characteristics. A case study is presented to demonstrate the effectiveness and applicability of the KDD approach for performance evaluation of complex systems. The data mining tools utilized are general purpose, public domain and independent of the specific performance database involved. We are currently implementing the proposed KDD framework within an end-to-end performance evaluation system for designing complex parallel and distributed systems referred to as POEMS.