Design space exploration of reliable networked embedded systems

  • Authors:
  • Thilo Streichert;Michael Glaí;Christian Haubelt;Jürgen Teich

  • Affiliations:
  • Department of Computer Science 12, University of Erlangen-Nuremberg, Am Weichselgarten 3, 91058 Erlangen, Germany;Department of Computer Science 12, University of Erlangen-Nuremberg, Am Weichselgarten 3, 91058 Erlangen, Germany;Department of Computer Science 12, University of Erlangen-Nuremberg, Am Weichselgarten 3, 91058 Erlangen, Germany;Department of Computer Science 12, University of Erlangen-Nuremberg, Am Weichselgarten 3, 91058 Erlangen, Germany

  • Venue:
  • Journal of Systems Architecture: the EUROMICRO Journal
  • Year:
  • 2007

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Abstract

In this paper, a new methodology is presented for topology optimization of networked embedded systems as they occur in automotive and avionic systems as well as wireless sensor networks. By introducing a model which is (1) suitable for heterogeneous networks with different communication bandwidths, (2) modeling of routing restrictions, and (3) flexible binding of tasks onto processors, current design issues of networked embedded systems can be investigated. On the basis of this model, the presented methodology firstly allocates the required resources which can be communication links as well as computational nodes and secondly binds the functionality onto the nodes and the data dependencies onto the links such that no routing restrictions will be violated or capacities on communication links will be exceeded. Due to the often error-prone communication in networks, we allow for routing each data dependency over multiple routes in the networks. With this strategy, our methodology is able to increase the reliability of the entire system. This reliability analysis is based on Binary Decision Diagrams (BDDs) and is integrated in our multi-objective design space exploration. By applying Evolutionary Algorithms, we are able to consider multiple objectives simultaneously during the optimization process and allow for a subsequent unbiased decision making. An experimental evaluation as well as a demonstration of a case study from the field of automotive electronics will show the applicability of the presented approach.