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Title:Exploring Design Configurations of System Models: From Simultaneous Simulation to Search Heuristics
Author(s):Gaonkar, Shravan
Subject(s):computer science
Abstract:Simulation is applied in numerous and diverse elds, such as manufacturing systems, communications and protocol design, nancial and economic engineering, operations research, design of transportation networks and systems, and so forth. The real utility of simulation lies in the ability to compare and evaluate alternative designs before actual implementation or deployment of a system. To perform a thorough analysis of a large number of congurations with varying system design parameter values, it is important to develop efficient simulation and design space exploration methods that can evaluate a large number of alternative system congurations quickly and accurately. In situations where it is practical to exhaustively explore design parameter space, we proposed a new approach, called Simultaneous Simulation of Alternative System Congurations (SSASC), to evaluate dependability models that combines adaptive uniformization in simulation with the SCMS technique. SSASC showed that a signicant speed-up can be achieved compared to traditional discrete-event simulation to evaluate all alternative congurations. The event set management using adaptive clock algorithm and efficient data structures to manage system model's state access and update enables ecient simulation. Using SSASC, design engineers can benet from quicker evaluation of their system designs with better accuracy (due to variance reduction) than traditional simulation approaches provide. In situations where complete design exploration is not practical, this dissertation provides an intelligent search space exploration technique to effieciently determine near optimal solutions. This dissertation provides a technique, called design solver (DS), to determine near-optimal designs using meta-search heuristics. DS achieves efficiency in exploring the design parameter space by first determining the parameter values that have major impact on the quality of the design solution, and then determining parameter values that further fine-tunes the quality of the design solution. That decomposition reduces the size of the search space, allowing DS algorithm to focus on the most relevant regions to achieve a near-optimal solution. In essence, this dissertation "develops algorithms and techniques that would enable an ecient methodology to compare large numbers of alternative configurations in order to speed-up the design evaluation and validation process".
Issue Date:2008-10
Genre:Technical Report
Other Identifier(s):UIUCDCS-R-2008-3010
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-23

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