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Propagation of Agent Performance Parameters in Wireless Sensor Networks

  • J. C. Cuevas-Martinez
  • J. Canada-Bago
  • J. A. Fernández-Prieto
  • M. A. Gadeo-Martos
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 89)

Abstract

Wireless sensor networks are composed of resource-constrained sensor nodes, powered by batteries, with limited CPU and memory, and wireless communication. In spite of the fact that sensor nodes are resource-constrained devices, several soft computing technologies have been adapted to them. In order to save battery, sensor nodes work in cycles based on awake and sleep modes. In this work we propose a method, based on a differential decision system, to calculate dynamic parameters that control the awake-sleep cycle in a multi-agent sensor structure and their propagation to other sensor nodes in a network. As an application of the proposed system, a sound pressure monitoring application is presented. Results have shown that the proposed method utilizes less work cycles than continuous measuring systems, saving battery and improving the lifetime of sensor nodes, with a reasonable lost of precision.

Keywords

Resource-constrained devices multi-agent systems wireless sensor networks 

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References

  1. 1.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cyirci, E.: Wireless sensor networks: A survey. Computer Networks 38(4), 393–422 (2002)CrossRefGoogle Scholar
  2. 2.
    Yick, Y., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Computer Networks 52(12, 22), 2292–2330 (2008)CrossRefGoogle Scholar
  3. 3.
    Cohen, R., Kapchits, B.: An optimal wake-up scheduling algorithm for minimizing energy consumption while limiting maximum delay in a mesh sensor network. IEEE/ACM Trans. Netw. 17(2), 570–581 (2009)CrossRefGoogle Scholar
  4. 4.
    Karlsson, B.: Intelligent Sensor Networks - an Agent-Oriented Approach. In: Workshop on Real-World Wireless Sensor Networks (2005)Google Scholar
  5. 5.
    Cuevas-Martinez, J.C., Gadeo-Martos, M.A., Fernandez-Prieto, J.A., Canada-Bago, J., Yuste-Delgado, A.J.: Wireless Intelligent Sensors Management Application Protocol-WISMAP. Sensors 10(6), 8827–8849 (2010)CrossRefGoogle Scholar
  6. 6.
    Wooldridge, M.: An Introduction to Multiagent Systems. Wiley, New York (2002)Google Scholar
  7. 7.
    Karl, H., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. John Wiley & Sons, Chichester (2005)CrossRefGoogle Scholar
  8. 8.
    Filipponi, L., Santini, S., Vitaletti, A.: Data Collection in Wireless Sensor Networks for Noise Pollution Monitoring. In: Proc. of the 4th IEEE International Conference on Distributed Computing in Sensor Systems, Santorini Island, Greece, pp. 492–497 (2008)Google Scholar
  9. 9.
    Tandon, N., Choudhury, A.: A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International 32(8), 469–480 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • J. C. Cuevas-Martinez
    • 1
  • J. Canada-Bago
    • 1
  • J. A. Fernández-Prieto
    • 1
  • M. A. Gadeo-Martos
    • 1
  1. 1.Telecommunication Engineering DepartmentUniversity of JaenLinaresSpain

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