---
_id: '37006'
abstract:
- lang: eng
  text: In this paper we present an approach for the configuration and reconfiguration
    of FlexRay networks to increase their fault tolerance. To guarantee a correct
    and deterministic system behavior, the FlexRay specification does not allow a
    reconfiguration of the schedapproachule during run time. To avoid the necessity
    of a complete bus restart in case of a node failure, we propose a reconfiguration
    using redundant slots in the schedule and/or combine messages in existing frames
    and slots, to compensate node failures and increase robustness. Our approach supports
    the developer to increase the fault tolerance of the system during the design
    phase. It is a heuristic, which, additionally to a determined initial configuration,
    calculates possible reconfigurations for the remaining nodes of the FlexRay network
    in case of a node failure, to keep the system working properly. An evaluation
    by means of realistic safety-critical automotive real-time systems revealed that
    it determines valid reconfigurations for up to 80% of possible individual node
    failures. In summary, our approach offers major support for the developer of FlexRay
    networks since the results provide helpful feedback about reconfiguration capabilities.
    In an iterative design process these information can be used to determine and
    optimize valid reconfigurations.
author:
- first_name: Kay
  full_name: Klobedanz, Kay
  last_name: Klobedanz
- first_name: Andreas
  full_name: König, Andreas
  last_name: König
- first_name: Wolfgang
  full_name: Müller, Wolfgang
  id: '16243'
  last_name: Müller
citation:
  ama: 'Klobedanz K, König A, Müller W. A Reconfiguration Approach for Faul-Tolerant
    FlexRay Networks. In: <i>Proceedings of DATE’11</i>. IEEE; 2011. doi:<a href="https://doi.org/10.1109/DATE.2011.5763022">10.1109/DATE.2011.5763022</a>'
  apa: Klobedanz, K., König, A., &#38; Müller, W. (2011). A Reconfiguration Approach
    for Faul-Tolerant FlexRay Networks. <i>Proceedings of DATE’11</i>. 2011 Design,
    Automation &#38; Test in Europe, Grenoble, France. <a href="https://doi.org/10.1109/DATE.2011.5763022">https://doi.org/10.1109/DATE.2011.5763022</a>
  bibtex: '@inproceedings{Klobedanz_König_Müller_2011, place={Grenoble, France}, title={A
    Reconfiguration Approach for Faul-Tolerant FlexRay Networks}, DOI={<a href="https://doi.org/10.1109/DATE.2011.5763022">10.1109/DATE.2011.5763022</a>},
    booktitle={Proceedings of DATE’11}, publisher={IEEE}, author={Klobedanz, Kay and
    König, Andreas and Müller, Wolfgang}, year={2011} }'
  chicago: 'Klobedanz, Kay, Andreas König, and Wolfgang Müller. “A Reconfiguration
    Approach for Faul-Tolerant FlexRay Networks.” In <i>Proceedings of DATE’11</i>.
    Grenoble, France: IEEE, 2011. <a href="https://doi.org/10.1109/DATE.2011.5763022">https://doi.org/10.1109/DATE.2011.5763022</a>.'
  ieee: 'K. Klobedanz, A. König, and W. Müller, “A Reconfiguration Approach for Faul-Tolerant
    FlexRay Networks,” presented at the 2011 Design, Automation &#38; Test in Europe,
    Grenoble, France, 2011, doi: <a href="https://doi.org/10.1109/DATE.2011.5763022">10.1109/DATE.2011.5763022</a>.'
  mla: Klobedanz, Kay, et al. “A Reconfiguration Approach for Faul-Tolerant FlexRay
    Networks.” <i>Proceedings of DATE’11</i>, IEEE, 2011, doi:<a href="https://doi.org/10.1109/DATE.2011.5763022">10.1109/DATE.2011.5763022</a>.
  short: 'K. Klobedanz, A. König, W. Müller, in: Proceedings of DATE’11, IEEE, Grenoble,
    France, 2011.'
conference:
  location: Grenoble, France
  name: 2011 Design, Automation & Test in Europe
date_created: 2023-01-17T09:09:25Z
date_updated: 2023-01-17T09:09:33Z
department:
- _id: '672'
doi: 10.1109/DATE.2011.5763022
keyword:
- Schedules
- Fault tolerant systems
- Redundancy
- Protocols
- Automotive engineering
- Genetic algorithms
language:
- iso: eng
place: Grenoble, France
publication: Proceedings of DATE'11
publisher: IEEE
status: public
title: A Reconfiguration Approach for Faul-Tolerant FlexRay Networks
type: conference
user_id: '5786'
year: '2011'
...
---
_id: '64055'
abstract:
- lang: eng
  text: A program for iterative fitting procedures to determine the NMR parameters
    from 51V solid-state MAS NMR spectra was developed. It contains options to use
    genetic algorithms and downhill-simplex optimizing procedures to extract the optimal
    parameter sets, which describe our spectra. As computational kernel the SIMPSON
    program is employed. Other kernels like SPINEVOLUTION are easily incorporable.
    The algorithms are checked for their suitability for the present optimization
    problem and optimal simulation conditions are determined, with the focus on minimal
    processing time. The procedure leads to a very good agreement between experimental
    and simulated spectra in a passable period of time. First results for spectra
    of model compounds for the active site of vanadium haloperoxidases are presented.
author:
- first_name: Maria
  full_name: Waechtler, Maria
  last_name: Waechtler
- first_name: Annika
  full_name: Schweitzer, Annika
  last_name: Schweitzer
- first_name: Torsten
  full_name: Gutmann, Torsten
  id: '118165'
  last_name: Gutmann
- first_name: Hergen
  full_name: Breitzke, Hergen
  last_name: Breitzke
- first_name: Gerd
  full_name: Buntkowsky, Gerd
  last_name: Buntkowsky
citation:
  ama: Waechtler M, Schweitzer A, Gutmann T, Breitzke H, Buntkowsky G. Efficient analysis
    of 51V solid-state MAS NMR spectra using genetic algorithms. <i>Solid State Nuclear
    Magnetic Resonance</i>. 2009;35(1):37–48. doi:<a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">10.1016/j.ssnmr.2008.11.003</a>
  apa: Waechtler, M., Schweitzer, A., Gutmann, T., Breitzke, H., &#38; Buntkowsky,
    G. (2009). Efficient analysis of 51V solid-state MAS NMR spectra using genetic
    algorithms. <i>Solid State Nuclear Magnetic Resonance</i>, <i>35</i>(1), 37–48.
    <a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">https://doi.org/10.1016/j.ssnmr.2008.11.003</a>
  bibtex: '@article{Waechtler_Schweitzer_Gutmann_Breitzke_Buntkowsky_2009, title={Efficient
    analysis of 51V solid-state MAS NMR spectra using genetic algorithms}, volume={35},
    DOI={<a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">10.1016/j.ssnmr.2008.11.003</a>},
    number={1}, journal={Solid State Nuclear Magnetic Resonance}, author={Waechtler,
    Maria and Schweitzer, Annika and Gutmann, Torsten and Breitzke, Hergen and Buntkowsky,
    Gerd}, year={2009}, pages={37–48} }'
  chicago: 'Waechtler, Maria, Annika Schweitzer, Torsten Gutmann, Hergen Breitzke,
    and Gerd Buntkowsky. “Efficient Analysis of 51V Solid-State MAS NMR Spectra Using
    Genetic Algorithms.” <i>Solid State Nuclear Magnetic Resonance</i> 35, no. 1 (2009):
    37–48. <a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">https://doi.org/10.1016/j.ssnmr.2008.11.003</a>.'
  ieee: 'M. Waechtler, A. Schweitzer, T. Gutmann, H. Breitzke, and G. Buntkowsky,
    “Efficient analysis of 51V solid-state MAS NMR spectra using genetic algorithms,”
    <i>Solid State Nuclear Magnetic Resonance</i>, vol. 35, no. 1, pp. 37–48, 2009,
    doi: <a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">10.1016/j.ssnmr.2008.11.003</a>.'
  mla: Waechtler, Maria, et al. “Efficient Analysis of 51V Solid-State MAS NMR Spectra
    Using Genetic Algorithms.” <i>Solid State Nuclear Magnetic Resonance</i>, vol.
    35, no. 1, 2009, pp. 37–48, doi:<a href="https://doi.org/10.1016/j.ssnmr.2008.11.003">10.1016/j.ssnmr.2008.11.003</a>.
  short: M. Waechtler, A. Schweitzer, T. Gutmann, H. Breitzke, G. Buntkowsky, Solid
    State Nuclear Magnetic Resonance 35 (2009) 37–48.
date_created: 2026-02-07T16:15:57Z
date_updated: 2026-02-17T16:12:50Z
doi: 10.1016/j.ssnmr.2008.11.003
extern: '1'
intvolume: '        35'
issue: '1'
keyword:
- 51V MAS NMR spectroscopy
- Genetic algorithms
- Iterative fitting procedures
- Model complexes for vanadium haloperoxidases
language:
- iso: eng
page: 37–48
publication: Solid State Nuclear Magnetic Resonance
status: public
title: Efficient analysis of 51V solid-state MAS NMR spectra using genetic algorithms
type: journal_article
user_id: '100715'
volume: 35
year: '2009'
...