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Model-Driven Development of Self-organising Control Applications

  • Helge Parzyjegla
  • Arnd Schröter
  • Enrico Seib
  • Sebastian Holzapfel
  • Matthäus Wander
  • Jan Richling
  • Arno Wacker
  • Hans-Ulrich Heiß
  • Gero MühlEmail author
  • Torben Weis
Part of the Autonomic Systems book series (ASYS, volume 1)

Abstract

In this article we present a software development methodology and a supporting algorithm toolbox for Organic Computing applications that were developed in the context of the MODOC project. We focus on control applications for dynamic actuator/sensor networks that have no skilled human administrator and that are subject to frequent random hardware failures. To deal with these characteristics, applications in this setting should be self-organising and self-stabilising. However, realising self-organising and self-stabilising applications is usually a complex task requiring expert knowledge. Thus, we show that the development of such applications can be greatly simplified by shifting complexity into a model-driven tool chain. Developers implement their application in a high-level language based on a role abstraction focusing on application functionality. In order to hide the remaining complexity, we developed a tool chain which is responsible for transforming the high-level code to executable machine code that is automatically enriched by self-x properties such as self-organisation and self-stabilisation, which are not explicitly defined by the application programmer. Thereby, the application benefits from extended fault-tolerance and availability. A major part of the tool chain is a toolbox containing self-x algorithms commonly required for Organic Computing applications. The heart of the toolbox is an algorithm stack realised by our publish/subscribe middleware Rebeca that is able to efficiently realise self-organisation even in case of large networks.

Keywords

Model-driven development Publish/subscribe Self-stabilisation Self-organisation Actuator and sensor networks Composite event detection Adaptive routing 

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Copyright information

© Springer Basel AG 2011

Authors and Affiliations

  • Helge Parzyjegla
    • 1
  • Arnd Schröter
    • 2
  • Enrico Seib
    • 1
  • Sebastian Holzapfel
    • 3
  • Matthäus Wander
    • 3
  • Jan Richling
    • 2
  • Arno Wacker
    • 3
  • Hans-Ulrich Heiß
    • 2
  • Gero Mühl
    • 1
    Email author
  • Torben Weis
    • 3
  1. 1.University of RostockRostockGermany
  2. 2.Berlin University of TechnologyBerlinGermany
  3. 3.University of Duisburg-EssenDuisburg/EssenGermany

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