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    Cost-based partitioning for distributed simulation of hierarchical modular DEVS models

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    azu_td_3090011_sip1_m.pdf
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    Author
    Park, Sunwoo
    Issue Date
    2003
    Keywords
    Engineering, Electronics and Electrical.
    Computer Science.
    Advisor
    Zeigler, Bernard P.
    
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    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    The main objective of this research is to design and implement a class of generic partitioning algorithms for hierarchical, modular Discrete Event Specification System (DEVS) models for distributed simulation. To attain the goal of this dissertation, a set of partitioning algorithms is designed using the cost analysis methodology. For more than a decade, abundant research has been conducted to develop partitioning algorithms that can find optimal, or reasonably acceptable, solutions for various partitioning problems. These employ methods such as simulated annealing, random partitioning, heuristic partitioning, and hierarchical clustering. In this dissertation, a new Generic Model Partitioning (GMP) algorithm for hierarchical modular DEVS models is proposed for distributed simulation. The GMP algorithm decomposes a given hierarchical model into a set of partition blocks and provides reasonable solutions for distinct partitioning problems based on a cost analysis methodology. It also minimizes model decomposition during the partitioning process and guarantees incremental quality of partitioning (QoP) improvements until a best partitioning is attained. A series of cost measures for cost generation, cost evaluation, and cost aggregation are introduced. Since a cost measure is a parametric method, subject to certain axioms, the proposed algorithm is generic and applicable any family of models provided there is a way to manipulate the appropriate cost information. A class of advanced algorithms derived from the GMP algorithm is also presented to tackle sophisticated issues associated with various distributed system configurations.
    Type
    text
    Dissertation-Reproduction (electronic)
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Electrical and Computer Engineering
    Degree Grantor
    University of Arizona
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