Advertisement

Topology Information Control in Feedback Based Reconfiguration Processes

  • Alexandru Murgu
  • Ian Postlethwaite
  • Dawei Gu
  • Chris Edwards
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 40)

Summary

In this paper, we describe an information control and coding framework devoted to reconfiguration processes based on a modified perspective on the Shannon information where the information flows are regarded as network commodities. This interpretation is suitable for independent multipoint-to-multipoint channels in group communication, such as the multiple-access or broadcast channels, and allows the flow control class of techniques to implement the information coding by invoking the multi-layered protocol stack. Iterative parametric dynamic programming is a good modeling candidate for describing the reconfiguration process as multi-objective relational optimization in a multilevel fashion. At the lower processing level, an auxiliary weighted power Lagrangian problem is solved using dynamic programming associated to the topology control. The upper processing level adjusts the value of the weighting vector in a weighted power Lagrangian formulation which is responsible for the information control monitoring. The low level solution process is repeated until the optimal solution of the nonseparable optimization problem is attained by the optimal solution of an auxiliary weighted power Lagrangian problem. The application of this information control framework is to the management traffic in self-healing networks of UAV surveillance missions.

Keywords

Span Tree Information Control Network Element Control Symbol Resource Reservation Protocol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Elston, J., Frew, E.W., Argrow, B.: Networked UAV communication, command, and control. In: Proc. AIAA Guidance, Navig., Contr. Conf. (2006) Google Scholar
  2. 2.
    Beard, R., McLain, T., Nelson, D., Kingston, D., Johanson, D.: Decentralized cooperative aerial surveillance using fixed-wing miniature UAVs. In: Proc. IEEE, vol. 94, no. 7, pp. 1306–1324 (2006) Google Scholar
  3. 3.
    Rezano, J., Mozos, D., Catthoor, F., Verkest, D.: A reconfiguration manager for dynamically reconfigurable hardware. In: IEEE Design and Test of Computers, pp. 452–460 (2005) Google Scholar
  4. 4.
    Ross, K.W.: Multiservice Loss Models for Broadband Telecommunication Networks. Springer, London (1995) MATHGoogle Scholar
  5. 5.
    Even, S., Tarjan, E.: Network flow and testing graph connectivity. SIAM J. Comput. 4, 507–518 (1975) MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    IEEE standard for local and metropolitan area networks: virtual bridged local area networks. IEEE Std 802.1Q-1998 Google Scholar
  7. 7.
    IEEE standard for local and metropolitan area networks—common specifications. Part 3: Media access control (MAC) bridges—amendment 2: Rapid reconfiguration amendment to IEEE Std 802.1D, 1998 Edition. IEEE Std 802.1w-2001 Google Scholar
  8. 8.
    Ahlswede, R., Cai, N., Li, S.-Y., Yeung, R.W.: Network information flow. IEEE Trans. Inf. Theory 46(4), 1204–1216 (2000) MATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Cover, T.M., Thomas, J.: Elements of Information Theory. Wiley, New York (1991) MATHCrossRefGoogle Scholar
  10. 10.
    Berger, T.: The Information Theory Approach to Communications. Springer, Berlin (1978) MATHGoogle Scholar
  11. 11.
    Even, G., Even, S.: Embedding interconnection networks in grid via the layered cross product. Networks 36(2), 91–95 (2000) MATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Duato, J., Yalamanchili, S., Ni, L.: Interconnection Networks: An Engineering Approach. IEEE Comput. Soc., Silver Spring (1997) Google Scholar
  13. 13.
    Bertsekas, D.: Nonlinear Programming. Athena Scientific, Belmont (1995) MATHGoogle Scholar
  14. 14.
    Fletcher, R.: Practical Method of Optimization. Wiley, New York (1987) Google Scholar
  15. 15.
    Wolinski, C., Kuchcinski, K.: Automatic selection of application-specific reconfigurable processor extensions. In: DATE 2008: Proc. of the Conf. on Design, Automation and Test in Europe, pp. 1214–1219 (2008) Google Scholar
  16. 16.
    Henriksen, S.J.: Estimation of future communications bandwidth requirements for unmanned aircraft systems operating in the national airspace system. In: Proc. AIAA InfoTech@Aerospace, vol. 3, pp. 2746–2754 (2007) Google Scholar
  17. 17.
    Dixon, C., Frew, E.W.: Decentralized extremum-seeking control of nonholonomic vehicles to form a communication chain. In: M.J. Hirsch, P.M. Pardalos, R. Murphey, D. Grundel (eds.), Advances in Cooperative Control and Optimization. Lecture Notes in Control and Information Sciences, vol. 369, pp. 311–322 (2007) Google Scholar
  18. 18.
    Vasseur, J.-P., Pickavet, M., Demeester, P.: Network Recovery, Protection and Restoration of Optical, SONET-SDH, IP, and MPLS. Morgan Kaufman, Amsterdam (2004) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Alexandru Murgu
    • 1
  • Ian Postlethwaite
    • 1
  • Dawei Gu
    • 1
  • Chris Edwards
    • 1
  1. 1.Department of Engineering, Control and Instrumentation GroupUniversity of LeicesterLeicesterUK

Personalised recommendations