Abstract
Wireless Sensor Networks (WSNs) are generally composed of a large number of battery operated nodes with limited capacities. Therefore, a main challenge in the management of a WSN is how to reduce the energy consumption while maintaining a good quality of the sensed data. Artificial intelligence techniques like multiagent coalition formation can help on this. In this paper we propose an algorithm called Coalition Oriented Sensing Algorithm and test it in a realistic scenario. We experimentally show how this new algorithm allows nodes to self-organise: nodes perform a good monitoring of the environment while maximising the life span of the overall sensor network.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Sims, M., Goldman, C.V., Lesser, V.: Self-organization through bottom-up coalition formation. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2003, pp. 867–874. ACM, New York (2003)
Mac Ruairí, R., Keane, M.T.: The dynamic regions theory: Role based partitioning for sensor network optimization. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (2007)
Gaston, M.E.: desJardins, M.: Agent-organized networks for dynamic team formation. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2005, pp. 230–237. ACM, New York (2005)
Barton, L., Allan, V.H.: Methods for Coalition Formation in Adaptation-Based Social Networks. In: Klusch, M., Hindriks, K.V., Papazoglou, M.P., Sterling, L. (eds.) CIA 2007. LNCS (LNAI), vol. 4676, pp. 285–297. Springer, Heidelberg (2007)
Glinton, R., Scerri, P., Sycara, K.: Agent-based sensor coalition formation. In: 2008 11th International Conference on Information Fusion, pp. 1–7 (July 2008)
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, HICSS 2000, vol. 8, p. 8020. IEEE Computer Society, Washington, DC (2000)
Bandyopadhyay, S., Coyle, E.J.: An energy efficient hierarchical clustering algorithm for wireless sensor networks. In: Proceedings of IEEE INFOCOM 2003, pp. 1713–1723 (April 2003)
Younis, O., Fahmy, S.: Heed: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing 3, 366–379 (2004)
Cordina, M., Debono, C.J.: Maximizing the lifetime of wireless sensor networks through intelligent clustering and data reduction techniques. In: Proceedings of the 2009 IEEE Conference on Wireless Communications & Networking Conference, WCNC 2009, pp. 2508–2513. IEEE Press, Piscataway (2009)
Padhy, P., Dash, R.K., Martinez, K., Jennings, N.R.: A utility-based sensing and communication model for a glacial sensor network. In: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2006, pp. 1353–1360. ACM, New York (2006)
Dyo, V., Ellwood, S.A., Macdonald, D.W., Markham, A., Mascolo, C., Pásztor, B., Scellato, S., Trigoni, N., Wohlers, R., Yousef, K.: Evolution and sustainability of a wildlife monitoring sensor network. In: SenSys, pp. 127–140 (2010)
IIIA-CSIC: Repast sensor network simulation toolkit (2012), http://www.iiia.csic.es/~mpujol/RepastSNS/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
del Carmen Delgado-Roman, M., Pujol-Gonzalez, M., Sierra, C. (2013). Multiagent Co-ordination of Wireless Sensor Networks. In: Nin, J., Villatoro, D. (eds) Citizen in Sensor Networks. CitiSens 2012. Lecture Notes in Computer Science(), vol 7685. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36074-9_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-36074-9_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36073-2
Online ISBN: 978-3-642-36074-9
eBook Packages: Computer ScienceComputer Science (R0)