A Model Integrated Framework for Designing and Optimization of Self-managing Computing Systems
Bai, Jia
:
2008-07-26
Abstract
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.