Back to search

Virginia Tech

A Runtime Framework for Adaptive Compositional Modeling

Abstract

dc:description.abstract

The rapid emergence of embedded devices and sensor networks that frequently exchange object-level images foretells an increasing reliance on object-level systems. Additionally, nearly all computing systems, including control systems, enterprise applications, scientific codes and dynamic libraries operate eventually at the object code level. Studying adaptivity and runtime composition issues in such systems is becoming an important focus of systems research. In this thesis, we describe an object-level framework that will manipulate an object module to instrument control functionality and adaptivity in order to realize complex compositional scenarios. Using function and parameter remapping capabilities, our framework transcends programming language and design boundaries, and enables applications to adapt dynamically during runtime. We introduce the capability to "restart" an application automatically, a feature we utilize to support adaptivity not only spatially, over the algorithm domain, but temporally as well. A high-level adaptive control language based on XML is presented that allows complex adaptive scenarios to be expressed concisely. Additionally, the construction of several adaptive scenarios using our framework is illustrated, along with several experiments in ``learning adaptivity`` using reinforcement learning techniques.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2004

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Heffner, Michael Alan
Chairs dc:contributor.committeechair
  • Varadarajan, Srinidhi
  • Ramakrishnan, Naren
Committee member dc:contributor.committeemember
  • Ribbens, Calvin J.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-05162004-212101
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/9921

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Heffner, Michael Alan. A Runtime Framework for Adaptive Compositional Modeling. masters thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9921