Framework for the Performance Assessment of Architectural Options on Intelligent Distributed Applications

Abstract

This position paper brings together the evaluation of ambient intelligence architectures in context-awareness systems with performance modeling. Thus, firstly appropriate description methods for distributed intelligent applications are summarized. Derived from the system characterization, typical software performance engineering techniques are based on the augmented description of the model regarding performance annotations. However, these annotations are only related with the syntactical view of the architecture. In the next generation of performance assessment tools for intelligent context-awareness systems, the description of the system would be capable of reasoning and acquiring knowledge about performance. Having an appropriate architectural description including performance aspects, any possible design options for intelligent distributed applications can be evaluated according to their performance impact. Therefore, we propose the use of an ontology with performance-related information - not only to evaluate the architecture off-line - but also building a context broker that assesses the performance during execution.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA515695

Entities

People

  • Carlos Juiz
  • Christian Kurz
  • Gunter Haring
  • Joachim Zottl
  • Ramon Puigjaner

Organizations

  • University of Vienna

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computer Programming
  • Computer Science
  • Computers
  • Engineering
  • Language
  • Mobile Computing
  • Mobile Devices
  • Mobile Phones
  • Mobile Software
  • Ontologies
  • Performance Engineering
  • Personal Digital Assistants
  • Software Design
  • Software Development
  • Standards
  • Tablet Computers
  • Ubiquitous Computing

Fields of Study

  • Computer science
  • Engineering

Readers

  • Artificial Intelligence
  • Computer Science.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.