University of Notre Dame
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Autonomic Web-based Simulation

thesis
posted on 2005-03-03, 00:00 authored by Yingping Huang
Many scientific and engineering simulations are large programs which despite careful debugging and testing will probably contain errors when deployed to the Web for use. Based on the assumption that such scientific and engineering simulations do contain errors and that the underlying computing systems do fail due to hardware or software errors, we present a framework called autonomic web-based simulation (AWS), a supporting data warehouse, and their implementations to develop and deploy reliable web-based simulations. AWS strives to achieve the following features presented in the Vision of Autonomic Computing: self-configuring, self-optimizing, self-healing and self-protecting. We discuss mathematical models to simulate the execution of scientific simulations and formulate objective functions for the purpose of determining optimal checkpoint intervals. Checkpointing is a basic requirement for self-healing of AWS and determining optimal checkpoint interval helps achieve self-optimizing of AWS. A novel three step data cleansing algorithm is designed through approximate string joins. A self-manageable system is implemented for the NOM simulation project which allows scientists and other end users run NOM simulations anytime from anywhere.

History

Date Modified

2017-06-05

Defense Date

2005-03-21

Research Director(s)

Martin Haenggi

Committee Members

Mark Alber Keven Bowyer Gregory Madey Patrick Flynn

Degree

  • Doctor of Philosophy

Degree Level

  • Doctoral Dissertation

Language

  • English

Alternate Identifier

etd-03032005-102812

Publisher

University of Notre Dame

Additional Groups

  • Computer Science and Engineering

Program Name

  • Computer Science and Engineering

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