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Model-driven Self-optimization Using Integer Linear Programming and Pseudo-Boolean Optimization

Authors:
Sebastian Götz
Claas Wilke
Sebastian Richly
Christian Piechnick
Georg Püschel
Uwe Assmann

Keywords: self-adaptive systems; integer linear programming; pseudo-boolean optimization; MDSD

Abstract:
The development of self-optimizing software systems usually requires developers to apply optimization techniques manually, which is time consuming and prone to error. The application of model-driven software development combined with models at runtime takes this burden from developers by generating optimization problems using model transformations. In this paper, we present two such approaches applying integer linear programming and pseudo-boolean optimization. Furthermore, we provide a scalability analysis of both approaches showing their feasibility for pipe-and-filter applications.

Pages: 55 to 64

Copyright: Copyright (c) IARIA, 2013

Publication date: May 27, 2013

Published in: conference

ISSN: 2308-4146

ISBN: 978-1-61208-274-5

Location: Valencia, Spain

Dates: from May 27, 2013 to June 1, 2013