OASiS: A Service-Oriented Architecture for Ambient-Aware Sensor Networks

  • Xenofon Koutsoukos
  • Manish Kushwaha
  • Isaac Amundson
  • Sandeep Neema
  • Janos Sztipanovits
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4888)


Heterogeneous sensor networks are comprised of ensembles of small, smart, and cheap sensing and computing devices that permeate the environment, as well as resource intensive sensors such as satellite imaging systems, meteorological stations, and security cameras. Emergency response, homeland security, and many other applications have a very real need to interconnect these diverse networks and access information in real-time. Web service technologies provide well-developed mechanisms for exchanging data between heterogeneous computing devices, but they cannot be used in resource-constrained wireless sensor networks. This paper presents OASiS, a lightweight service-oriented architecture for sensor networks, which provides dynamic service discovery and can be used to develop ambient-aware applications that adapt to changes in the network and the environment. An important advantage of OASiS is that it allows seamless integration with Web services. We have developed a middleware implementation that supports OASiS, and a simple tracking application to illustrate the approach. Our results demonstrate the feasibility of a service-oriented architecture for wireless sensor networks.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: A Survey. IEEE Computer 38(4), 393–422 (2002)Google Scholar
  2. 2.
    Yarvis, M., Kushalnagar, N., Singh, H., Rangarajan, A., Liu, Y., Singh, S.: Exploiting Heterogeneity in Sensor Networks. In: INFOCOM. Proceedings of the 24th Annual IEEE International Conference on Computer Communiation (March 2005)Google Scholar
  3. 3.
    Duarte-Melo, E., Liu, M.: Analysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks. In: Globecom. Proceedings of the 45th Annual IEEE Global Communications Conference (2002)Google Scholar
  4. 4.
    Lazos, L., Poovendran, R., Ritcey, J.A.: Probabilistic Detection of Mobile Targets in Heterogeneous Sensor Networks. In: IPSN. Proceedings of the 6th International Conference on Information Processing in Sensor Networks (2007)Google Scholar
  5. 5.
    Liu, J., Zhao, F.: Towards Semantic Services for Sensor-rich Information Systems. In: BaseNets. Proceedings of the 2nd IEEE/CreateNet International Workshop on Broadband Advanced Sensor Networks (2005)Google Scholar
  6. 6.
    Luo, L., Abdelzaher, T., He, T., Stankovic, J.: EnviroSuite: An Environmentally Immersive Programming System for Sensor Networks. ACM Transactions on Embedded Computing Systems 5(3), 543–576 (2006)CrossRefGoogle Scholar
  7. 7.
    Booth, D., Haas, H., McCabe, F., Newcomer, E., Champion, M., Ferris, C., Orchard, D.: Web Services Architecture, http://www.w3.org/TR/ws-arch/
  8. 8.
    Welch, G., Bishop, G.: An Introduction to the Kalman Filter. Technical Report TR 95-041, Department of Computer Science, University of North Carolina at Chapel Hill (2004)Google Scholar
  9. 9.
    Cheong, E., Liebman, J., Liu, J., Zhao, F.: TinyGALS: A Programming Model for Event-driven Embedded Systems. In: SAC. Proceedings of the 18th Annual ACM Symposium on Applied Computing (2003)Google Scholar
  10. 10.
    Engelstad, P., Zheng, Y.: Evaluation of Service Discovery Architectures for Mobile Ad Hoc Networks. In: WONS. Proceedings of the 2nd Annual Conference on Wireless On Demand Network Systems and Services (2005)Google Scholar
  11. 11.
    Johnson, D.B., Maltz, D.A.: Dynamic Source Routing in Ad Hoc Wireless Networks. In: Imielinski, T., Korth, H. (eds.) Mobile Computing, Kluwer Academic Publishers, Dordrecht (1996)Google Scholar
  12. 12.
    Regin, J.C.: A Filtering Algorithm for Constraints of Difference in CSPs. In: Proceedings of the 12th National Conference on Artificial Intelligence, vol. 1 (1994)Google Scholar
  13. 13.
    Guibas, L.J.: Sensing, Tracking, and Reasoning with Relations. IEEE Signal Processing Magazine (March 2002)Google Scholar
  14. 14.
    Baase, S., Gelder, A.V.: Computer Algorithms: Introduction to Design and Analysis, 3rd edn. Addison-Wesley, Reading (1999)Google Scholar
  15. 15.
    Universal Description, Discovery, and Integration, http://www.uddi.org
  16. 16.
  17. 17.
  18. 18.
    Levis, P., Madden, S., Gay, D., Polastre, J., Szewczyk, R., Woo, A., Brewer, E., Culler, D.: The Emergence of Networking Abstractions and Techniques in TinyOS. In: NSDI. Proceedings of the 1st Symposium on Networked Systems Design and Implementation (2004)Google Scholar
  19. 19.
    Cheong, E., Liu, J.: galsC: A Language for Event-driven Embedded Systems. In: DATE. Proceedings of the Conference on Design, Automation and Test in Europe (2005)Google Scholar
  20. 20.
    Gay, D., Levis, P., von Behren, R., Welsh, M., Brewer, E., Culler, D.: The nesC Language: A Holistic Approach to Networked Embedded Systems. In: PLDI. Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (2003)Google Scholar
  21. 21.
    Apache Web Services, http://ws.apache.org/
  22. 22.
    Simon, G., Volgyesi, P., Maroti, M., Ledeczi, A.: Simulation-based Optimization of Communication Protocols for Large-scale Wireless Sensor Networks. In: IEEE Aerospace Conference (2003)Google Scholar
  23. 23.
    Hadim, S., Mohamed, N.: Middleware: Middleware Challenges and Approaches for Wireless Sensor Networks. IEEE Distributed Systems Online 7 (2006)Google Scholar
  24. 24.
    Bakshi, A., Prasanna, V., Reich, J., Larner, D.: The Abstract Task Graph: A Methodology for Architecture-independent Programming of Networked Sensor Systems. In: EESR. Workshop on End-to-end, Sense-and-respond Systems, Applications, and Services (2005)Google Scholar
  25. 25.
    Fok, C.L., Roman, G.C., Lu, C.: Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications. In: ICDCS. Proceedings of the 25th International Conference on Distributed Computing Systems (2005)Google Scholar
  26. 26.
    Dedecker, J., Cutsem, T.V., Mostinckx, S., D’Hondt, T., Meuter, W.D.: Ambient-oriented Programming. In: OOPSLA. Proceedings of the 20th Annual Conference on Object-oriented Programming, Systems, Languages, and Applications (2005)Google Scholar
  27. 27.
    Baird, S., Dawson-Haggerty, S., Myung, D., Gaynor, M., Welsh, M., Moulton, S.: Communicating Data from Wireless Sensor Networks Using the hl7v3 Standard. In: BSN. International Workshop on Wearable and Implantable Body Sensor Networks (2006)Google Scholar
  28. 28.
    Kogekar, S., Neema, S., Eames, B., Koutsoukos, X., Ledeczi, A., Maroti, M.: Constraint-guided Dynamic Reconfiguration in Sensor Networks. In: IPSN. Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks (2004)Google Scholar
  29. 29.
    Heinzelman, W.B., Murphy, A.L., Carvalho, H.S., Perillo, M.A.: Middleware to Support Sensor Network Applications. IEEE Network 18(1), 6–14 (2004)CrossRefGoogle Scholar
  30. 30.
    Borcea, C., Iyer, D., Kang, P., Saxena, A., Iftode, L.: Spatial Programming Using Smart Messages: Design and Implementation. In: ICDCS. Proceedings of the 24th International Conference on Distributed Computing Systems (2004)Google Scholar
  31. 31.
    Borcea, C., Iyer, D., Kang, P., Saxena, A., Iftode, L.: Cooperative Computing for Distributed Embedded Systems. In: ICDCS. Proceedings of the 22nd International Conference on Distributed Computing Systems (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xenofon Koutsoukos
    • 1
  • Manish Kushwaha
    • 1
  • Isaac Amundson
    • 1
  • Sandeep Neema
    • 1
  • Janos Sztipanovits
    • 1
  1. 1.Institute for Software Integrated Systems, Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee 37235USA

Personalised recommendations