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A Convex Optimization-Based Approach to Control of Uncertain Execution Platforms

Lindberg, Mikael LU (2010) 49th IEEE Conference on Decision and Control p.2322-2329
Abstract
The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perfor- mance analysis through simulations. An implementation of the approach is experimentally compared with a static analysis scheme using worst case a-priori estimates. It is demonstrated that the presented approach outperforms the static scheme in situations with uncertainty and that the advantage increases as uncertainty grows.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to conference
publication status
published
subject
pages
2322 - 2329
conference name
49th IEEE Conference on Decision and Control
external identifiers
  • WOS:000295049102108
  • Scopus:79953148903
language
English
LU publication?
yes
id
4dd6cf7b-5429-4d7a-9e7e-8754440d6db6 (old id 1786766)
date added to LUP
2011-02-14 11:37:22
date last changed
2016-10-13 04:58:00
@misc{4dd6cf7b-5429-4d7a-9e7e-8754440d6db6,
  abstract     = {The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perfor- mance analysis through simulations. An implementation of the approach is experimentally compared with a static analysis scheme using worst case a-priori estimates. It is demonstrated that the presented approach outperforms the static scheme in situations with uncertainty and that the advantage increases as uncertainty grows.},
  author       = {Lindberg, Mikael},
  language     = {eng},
  pages        = {2322--2329},
  title        = {A Convex Optimization-Based Approach to Control of Uncertain Execution Platforms},
  year         = {2010},
}