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Title page for ETD etd-07222008-152758

Type of Document Master's Thesis
Author Bai, Jia
Author's Email Address jia.bai@vanderbilt.edu
URN etd-07222008-152758
Title A Model Integrated Framework for Designing and Optimization of Self-managing Computing Systems
Degree Master of Science
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Gabor Karsai Committee Member
Sherif Abdelwahed Committee Member
  • Model-integrated computing
  • Automatic control
  • control theory
  • Artificial intelligence
  • search algorithms
  • GME
Date of Defense 2008-07-25
Availability unrestricted
This thesis addresses the problem of managing computing systems using an

integration of model-based control techniques and efficient AI search

strategies. The proposed control approach uses the system model to forecast all

future system behavior up to a certain horizon and then searches for the best

path for the system based on a given utility function. In practical computing

systems, however, the large number of control (tuning) options directly affects

the computational overhead of the control module which executes in the

background at run-time, and ultimately slows down the overall system. To handle

this problem, several search algorithms are introduced to improve the

controller's performance.

This thesis also presents a model integrated framework, referred to as the Automatic

Control Modeling Environment (ACME), to facilitate the use of control-based

technology for self-management in computation systems. Control-theoretic concepts like above have been investigated and applied successfully to automate the management of computation systems of the control technology. ACME is a

domain-specific graphical modeling environment with automated synthesis tools.

The framework allows domain engineers to develop models for general computation

systems and to capture their performance requirements and operational

constraints. The framework can automatically generates executable codes for the

controllers based on the given system model and specifications.

A case study of

an online processor power management is used to demonstrate the effectiveness of the new search techniques for the model-based control approach as well as the application of the ACME.

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