Optimal Control and Management

Project Overview

The focus of our research in this project concerns the control and optimization of performance and other measures in stochastic queueing networks. As a particular application area, we are interested in the analysis and optimization of the performance of Web servers and Web applications. Recent and emerging applications, e.g., those based on the Internet, have raised issues regarding differentiated service and quality of service based on non-traditional metrics, e.g., service-level-agreements based on distributions as opposed to averages. This together with the complex arrival and service processes found in practice make many of the optimal control and resource allocation problems extremely difficult. Our research has established provably optimal control policies for various queueing networks, in some cases based on asymptotic solutions.

Issues We Concerned

By deploying various mathematical studies using Queueing Theory, Probabilistic Modeling, Stochastic Scheduling and Control Theory etc, we provide solutions to theoretical issues related to areas such as quality of service, scalability, dynamic scheduling algorithms, load balancing, admission control, buffer management, inventory management, profit and risk management, and service-level-agreements based on response-time distributions. In turn, these theoretical results have been further exploited to develop practical solutions for performance problems in many different areas of research, including traffic generation and benchmarking, model validation, capacity planning, workload and performance forecasting, power-consumption models, generating and serving dynamic content, resource control and management, cooperative caching, dynamic offload, and network and server design.

People

• Zhen Liu
• Mark S. Squillante
• Joel L. Wolf
• Cathy H. Xia
• Shun-zheng Yu
• Li Zhang

Recent Publications

 Publications in journals

 Papers in proceedings of international conferences