Performance modeling and analysis has been and continues to be of great practical and theoretical importance in research labs in the design, development and optimization of computer and communication systems and applications. This includes a broad spectrum of research activities from the use of more empirical methods (ranging from experimental tweaking of simple existing models up to building and experimenting with prototype implementations) through the use of simulation to more sophisticated mathematical methods.
IBM Research has a distinguished history in the theory and practice of performance analysis, modeling and optimization. Fundamental and foundational contributions have been made in a number of important areas, including: product-form queueing networks; optimal control and scheduling in queueing networks; stochastic ordering and majorization; rare-event and parallel simulation; matrix-analytic analysis of stochastic models; polling systems; and performance modeling tools. These have played a critical role in understanding important problems in the design, development, management and planning of complex systems.
Projects
- Mathematical Modeling and Analysis
To explore and solve fundamental, theoretical problems in areas including mathematical analysis of system/application data
- Optimal Control and Management
To explore techniques for the control and optimization of performance and other measures in stochastic queueing networks.
- Page Detailer
- Performance Management
- Performance, Scalability, and Reliability of Middleware Systems
- Web Performance
- Wide-Area Server Performance