Skip to main content
Log in

Power-aware agent-solution for information communication in WSN

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

The information-communication in an energy efficient and scalable manner in a wireless sensor network is a basic need. In this work, we use the multi-agent approach in order to build an Information Importance Based Communication (IIBC) for large scale wireless sensor network data processing. A multi-agent cooperation can be used to greatly reduce the communication cost, especially over low bandwidth links, by treating data cooperatively in sensor nodes rather than bringing this data to a central processor. The principal goal of our proposition is to maximize the wireless sensor network life time and simultaneously to insure a sufficient level of performance in term of latency, packet loss and reliability. Through successive simulations, IIBC proved its ability to reduce the power consumption of the sensor node to maximize “the mean time to first network partition” in several network densities and scales.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Chen, M., Kwon, T., Yuan, Y., & Leung, V. C. M. (2006). Mobile agent based wireless sensor networks. Journal of Computers 14–21.

  2. Ruairí, R. M., & Keane, M. T. (2007). An energy-efficient multi-agent sensor network for detecting diffuse events. In IJCAI’07: Proceedings of the 20th international joint conference on artifical intelligence (pp. 1390–1395). San Mateo: Morgan Kaufmann.

    Google Scholar 

  3. Marsh, D., O’Kane, D., & O’Hare, G. M. P. (2005). Agents for wireless sensor network power management. In ICPPW ’05: proceedings of the 2005 international conference on parallel processing workshops (pp. 413–418). Washington: IEEE Computer Society.

    Google Scholar 

  4. Gan, L., Liu, J., & Jin, X. (2004). Agent-based energy efficient routing in sensor networks. In AAMAS ’04: proceedings of the third international joint conference on autonomous agents and multiagent systems (pp. 472–479). Washington: IEEE Computer Society.

    Google Scholar 

  5. Mistry, O., Gürsel, A., & Sen, S. (2009). Comparing trust mechanisms for monitoring aggregator nodes in sensor networks. In AAMAS ’09: proceedings of the 8th international conference on autonomous agents and multiagent systems, Richland, SC (pp. 985–992). International Foundation for Autonomous Agents and Multiagent Systems.

  6. Johnson, D., Hu, Y., & Maltz, D. (2007). The dynamic source routing protocol (DSR) for placeMobile ad hoc networks for IPv4 (Technical report).

  7. Chou, J., Petrovic, D., & Ramchandran, K. (2002). Tracking and exploiting correlations in dense sensor networks. In Conference record of the thirty-sixth asilomar conference on signals, systems and computers (pp. 39–43).

  8. Chou, J., Petrovic, D., & Ramchandran, K. (2003). A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks. In Twenty-second annual, joint conference of the ieee computer and communications societies (pp. 1054–1062).

  9. Swapnil, P., Samir, D., Asis, N. (2004). Serial data fusion using space-filling curves in wireless sensor networks. In First annual IEEE communications society conference on sensor and ad hoc communications and networks (pp. 182–190).

  10. Liao, W. H., Kao, Y., & Fan, C. M. (2008). Data aggregation in wireless sensor networks using ant colony algorithm. Journal of Network and Computer Applications, 31(4), 387–401.

    Article  Google Scholar 

  11. Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579–3585.

    Article  Google Scholar 

  12. Lang, T., Qing, Z., & Srihari, A. (2003). Sensor networks with mobile agents. In The IEEE military communications conference (pp. 688–693). New York: IEEE Press.

    Google Scholar 

  13. Qi, H., Xu, Y., Wang, X. (2003). Mobile-agent-based collaborative signal and information processing in sensor networks. Proceedings of the IEEE, 91(8), 1172–1183.

    Article  Google Scholar 

  14. González-Valenzuela, S., Chen, M., & Leung, V. C. M. (2009). Design, implementation and case study of wiseman: wireless sensors employing mobile agents. In J. M. Bonnin, C. Giannelli, & T. Magedanz (Eds.), MOBILWARE. Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering (Vol. 7, pp. 366–380). Berlin: Springer.

    Google Scholar 

  15. Chen, M., González-Valenzuela, S., & Leung, V. C. M. (2007). Applications and design issues of mobile agents in wireless sensor networks. IEEE Wireless Communications Magazine, 14(6), 20–26.

    Article  Google Scholar 

  16. Sardouk, A., Rahim-Amoud, R., Merghem-Boulahia, L., & Gaïti, D. (2009). Information-importance based communication for large-scale WSN data processing. In WMNC. Gdansk: IFIP.

    Google Scholar 

  17. Sardouk, A., Merghem-Boulahia, L., & Gaïti, D. (2008). Agents cooperation for power-efficient information processing in wireless sensor networks. In Networking and electronic commerce research conference, Italy.

  18. Sardouk, A., Merghem-Boulahia, L., & Gaïti, D. (2008). Agent-cooperation based communication architecture for wireless sensor network. In IFIP wireless days/ad-hoc and wireless sensor networks. UAE: IFIP.

    Google Scholar 

  19. Brooks, R. (1985). A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2(1), 14–23.

    Article  Google Scholar 

  20. Rahim-Amoud, R., Merghem-Boulahia, L., & Gaïti, D. (2008). An Autonomic MPLS DiffServ-TE Domain. Whitestein Series in Software Agent Technologies and Autonomic Computing, 9, 149–168.

    Article  Google Scholar 

  21. Laboratory, U., & Laboratory, W. (2005). Glomosim: a scalable simulation environment for wireless and wired network systems. In The 3rd International Working Conference on Performance Modeling and Evaluation of Heterogeneous Networks.

  22. Sohraby, K., Minoli, D., & Znati, T. (2007). Wireless sensor networks, technology, protocols, and applications. New York: Willey.

    Book  Google Scholar 

  23. Sun (2008). Sun TM small programmable object technology (Sun SPOT) theory of operation (Technical report). Sun Microsystem, Sun Labs.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmad Sardouk.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sardouk, A., Rahim-Amoud, R., Merghem-Boulahia, L. et al. Power-aware agent-solution for information communication in WSN. Telecommun Syst 48, 329–338 (2011). https://doi.org/10.1007/s11235-010-9347-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-010-9347-6

Keywords

Navigation