On the Design of Efficient Simulations for Complex Queuing Networks

• Activity Number: 47
• Type: Contributed
• Date/Time: Sunday, August 11, 2002 : 4:00 PM to 5:50 PM
• Sponsor: General Methodology
• Author(s): Ying-Chao Hung*+ and George Michailidis
• Affiliation(s): University of Michigan and University of Michigan
• Keywords: Simulation ; Network performance ; Experimental design ; Regression tree ; Response surface

Abstract

Traditional network models have played an important role in providing insight in the dynamics of telecommunication, computer, and manufacturing systems. At the core of various modern technologies, such as database management systems, high-speed packet switching architectures, online computing, etc., one finds the fundamental features of Parallel and Distributed Processing systems. Such systems due to the interaction and sharing of resources exhibit highly complex dynamics that cannot be analyzed through analytical methods. An important tool for understanding the complex dynamics is simulation, which can provide insight into the behavior of a complex system by identifying the response surface of several performance measures, such as backlogs and delays. However, simulations of large systems are expensive in terms of CPU time and preparation of custom-made computer codes. Our objective here is to use the smallest possible number of simulation runs (input sites) to adequately capture the underlying response surface of interest. Borrowing the ideas from experimental design, we present a methodological framework for designing efficient simulations for complex networks.