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Concepts for Self-Adaptive and Self-Healing Networked Embedded Systems

  • Thilo Streichert
  • Christian Haubelt
  • Dirk Koch
  • Jürgen Teich
Part of the Understanding Complex Systems book series (UCS)

Summary

Networked embedded systems which operate in unattended areas with rare maintenance often make use of redundant resources for guaranteeing reliable service. In this paper, we will present novel concepts for dynamically partitioning and assigning functionality to software as well as hardware reconfigurable resources in a network. As a result, self-adaptive and self-healing systems emerge with a good tradeoff between redundancy and reliability. The proposed concepts are embedded in a three step approach, which 1.) reestablishes the functionality after a resource defect, 2.) optimizes the binding of the running tasks and 3.) creates new replicas of the tasks in the network. In this contribution, we will give an overview over all three parts, but focus on the second step. For this second step, called dynamic hardware/software partitioning, we will present algorithms, theoretical optimality bounds for workload distributions as well as experimental results.

self-adaptive self-healing fault tolerance reliability networks embedded systems 

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References

  1. 1.
    N. Budhiraja,K. Marzullo,F. B. Schneider,and S. Toueg. The primary-backup approach. ACM Press/Addison-Wesley Publishing Co.,New York, NY, USA,1993.Google Scholar
  2. 2.
    G. C. Buttazzo and J. Stankovic. Adding Robustness in Dynamic Preemptive Scheduling. In Responsive Computer Systems, 1995.Google Scholar
  3. 3.
    G. Cybenko. Dynamic Load Balancing for Distributed MemoryMultiprocessors. Journal of Parallel and Distributed Computing, 7:279–301, Oct. 1989.CrossRefGoogle Scholar
  4. 4.
    E. W. Dijkstra. Self-stabilizing Systems in Spite of Distributed Control. Communications of the ACM, 17(11):643–644, Nov. 1974.CrossRefzbMATHGoogle Scholar
  5. 5.
    S. Dolev. Self-stabilization. MIT Press, Cambridge, MA, USA, 2000.zbMATHGoogle Scholar
  6. 6.
    R. Elsäasser, A. Frommer, B. Monien, and R. Preis. Optimal and Alternating-Direction Loadbalancing Schemes. In Proc. of Euro-Par 99, Parallel Processing, pages 280–290, 1999.Google Scholar
  7. 7.
    C. Haubelt. Automatic Model-Based Design Space Exploration for Embedded Systems – A System Level Approach. PhD thesis, University of Erlangen-Nuremberg, Germany, July 2005.Google Scholar
  8. 8.
    V. Izosimov, P. Pop, P. Eles, and Z. Peng. Design Optimization of Time- and Cost-Constrained Fault-Tolerant Distributed Embedded Systems. In Proceedings of Design, Automation and Test in Europe, Munich, Germany, Mar. 2005.Google Scholar
  9. 9.
    V. Kianzad and S. S. Bhattacharyya. CHARMED: A Multi-Objective Co-Synthesis Framework for Multi-Mode Embedded Systems. In Proceedings of the 15th IEEE International Conference on Application-Specific Systems, Architectures and Processors (ASAP’04), pages 28–40, Galveston, U.S.A., Sept. 2004.Google Scholar
  10. 10.
    P. K. Lala. Self-Checking and Fault-Tolerant Digital Design. Technical report, San Francisco, 2001.Google Scholar
  11. 11.
    M. Laumanns, L. Thiele, K. Deb, and E. Zitzler. Combining convergence and diversity in evolutionary multi-objective optimization. Evolutionary Computation, 10(3):263–282, 2002.CrossRefGoogle Scholar
  12. 12.
    M. López-Vallejo and J. C. López. On the Hardware-Software Partitioning Problem: System Modeling and Partitioning Techniques. ACM Transactions on Design Automation of Electronic Systems, 8(3):269–297, July 2003.CrossRefGoogle Scholar
  13. 13.
    R. Lysecky and F. Vahid. A configurable logic architecture for dynamic hardware/software partitioning. In Proceedings of the conference on Design, automation and test in Europe, pages 480–485. IEEE Computer Society, 2004.Google Scholar
  14. 14.
    T. Moscibroda and R. Wattenhofer. Facility Location: Distributed Approximation. In 24th ACM Symposium on the Principles of Distributed Computing (PODC), Las Vegas, Nevada, USA, July 2005.Google Scholar
  15. 15.
    Y. Rabani, A. Sinclair, and R. Wanka. Local Divergence of Markov Chains and the Analysis of Iterative Load-Balancing Schemes. In Symp. on Foundations of Computer Science FOCS, 1998.Google Scholar
  16. 16.
    Re CoNets-Demonstrator, 2006. www.reconets.de.Google Scholar
  17. 17.
    G. Sitt, R. Lysecky, and F. Vahid. Dynamic Hardware/Software Partitioning: A First Approach. In Proceedings of Design Automation Conference 2003, Anaheim, California, Germany, June 2003.Google Scholar
  18. 18.
    T. Weis, H. Parzyjegla, M. A. Jaeger, and G. Mühl. Self-Organizing and Self-Stabilizing Role Assignment in Sensor/Actuator Networks. In The 8th International Symposium on Distributed Objects and Applications (DOA 2006), pages 1807–1824, Montpellier, France, Oct. 2006.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Thilo Streichert
    • 1
  • Christian Haubelt
    • 1
  • Dirk Koch
    • 1
  • Jürgen Teich
    • 1
  1. 1.Hardware-Software-Co-Design ChairUniversity of Erlangen-Nuremberg91058 ErlangenGermany

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