DySSCo - A Protocol for Dynamic Self-Organizing Service Coverage

  • Martin Lipphardt
  • Jana Neumann
  • Sven Groppe
  • Christian Werner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5343)

Abstract

Service oriented middleware draws a lot of attention in current research on sensor networks. The automatic distribution of services within a network and the preservation of this distribution is a fundamental aspect of network applications with self-x properties. The network gains the ability to react on mobility, network fragmentation, node failures and new user demands. This paper proposes a distributed self-organizing algorithm for service distribution and preservation of this distribution using demanded coverages for the services. After discussing the theory of the convergence of the algorithm, this paper presents a real-world deployment of a sensor network scenario and evaluates the performance of the algorithm.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Blumenthal, J., Handy, M., Golatowski, F., Haase, M., Timmermann, D.: Wireless sensor networks - new challenges in software engineering. In: Emerging Technologies and Factory Automation, Proceedings. ETFA 2003. IEEE Conference, vol. 1 (2003)Google Scholar
  2. 2.
    Boulis, A., Han, C.-C., Srivastava, M.B.: Design and implementation of a framework for efficient and programmable sensor networks. In: MobiSys 2003: Proceedings of the 1st international conference on Mobile systems, applications and services, pp. 187–200. ACM, New York (2003)Google Scholar
  3. 3.
    Fok, C.-L., Roman, G.-C., Lu, C.: Rapid development and flexible deployment of adaptive wireless sensor network applications. In: International Conference on Distributed Computing Systems, vol. 00, pp. 653–662 (2005)Google Scholar
  4. 4.
    Levis, P., Patel, N., Culler, D., Shenker, S.: Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks. In: First Symposium on Network Systems Design and Implementation, NSDI (2004)Google Scholar
  5. 5.
    Levis, P., Culler, D.: Maté: a tiny virtual machine for sensor networks. SIGOPS Oper. Syst. Rev. 36(5), 85–95 (2002)CrossRefGoogle Scholar
  6. 6.
    Lipphardt, M., Hellbrueck, H., Pfisterer, D., Ransom, S., Fischer, S.: Practical experiences on mobile inter-body-area-networking. In: Proceedings of the Second International Conference on Body Area Networks, BodyNets 2007 (2007)Google Scholar
  7. 7.
    Koutsoukos, X., Neema, S., Kushwaha, M., Amundson, I., Sztipanovits, J.: Oasis: A programming framework for service-oriented sensor networks. In: IEEE/Create-Net COMSWARE 2007 (January 2007)Google Scholar
  8. 8.
    Marin-Perianu, R., Scholten, H., Havinga, P.: Prototyping service discovery and usage in wireless sensor networks. In: Conference on Local Computer Networks (LCN), vol. 0, pp. 841–850 (2007)Google Scholar
  9. 9.
    Marron, P.J., Lachenmann, A., Minder, D., Hahner, J., Sauter, R., Rothermel, K.: Tinycubus: A flexible and adaptive framework for sensor networks. In: Proceeedings of the Second European Workshop on Wireless Sensor Networks, pp. 278–289 (2005)Google Scholar
  10. 10.
    Wittenburg, G., Schiller, J.: A survey of current directions in service placement in mobile ad-hoc networks. In: IEEE International Conference on Pervasive Computing and Communications, vol. 0, pp. 548–553 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Martin Lipphardt
    • 1
  • Jana Neumann
    • 2
  • Sven Groppe
    • 2
  • Christian Werner
    • 1
  1. 1.Institute of TelematicsUniversity of LuebeckGermany
  2. 2.Institute of Information SystemsUniversity of LuebeckGermany

Personalised recommendations