Abstract
As the number of Wireless Sensor Networks (WSNs) applications is anticipated to grow substantially in coming years, new and radical strategies for effectively managing such networks will be needed. One possibility involves endowing the network with an autonomic capability to dynamically adapt itself to the prevailing network operating conditions, even while communications sessions are active. This may involve the network adapting itself either partially or completely. The approach suggested in this paper proposes that a suite of intelligent agents autonomously monitor the various network nodes and, depending on the status of certain parameters, actively intervene to alter the scheduling mechanism used, thus ensuring continuous operation and stability of the network together with an an improved performance yield.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-540-32993-0_29
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Ruzzelli, A., Evers, L., Dulman, S., Hoesel, L.V., Havinga, P.: On the design of an energy-efficient low-latency integrated protocol for distributed mobile sensor networks. In: IWWAN International Workshop on Wireless Ad hoc Networks (2004)
Ye, W., Heidemann, J., Estrin, D.: Medium access control with coordinated adaptive sleeping for wireless sensor networks. In: Twenty-First AnnualJoint conference of the IEEE Computer and Communication Societies (INFOCOM), vol. 3, pp. 1567–1576 (2002)
Rajendran, Obrazka, Garcia-Luna-Aceves: Energy-efficient, collision-free medium access control for wireless sensor netwoks. In: Conference on Embedded Networked Sensor System, pp. 181–192 (2003)
Dam, T.V., Langendoen, K.: An adaptive energy efficient mac protocol for wireless sensor networks. ACM Sensys (2003)
Hoiydi, A.E., Decotignie, J.: Wisemac: An ultra low power mac protocol for multi-hop wireless sensor networks. In: Nikoletseas, S.E., Rolim, J.D.P. (eds.) ALGOSENSORS 2004. LNCS, vol. 3121, pp. 18–31. Springer, Heidelberg (2004)
Johnson, D.B., Maltz, D.A.: Dinamic source routing in ad hoc wireless networks. In: Mobile computing, vol. 353. Kluwer Academic publishers, Dordrecht (1996)
Akan, O.B., Akyildiz, I.F., Sankarasubramaniam, Y.: Event-to-sink reliable transport in wireless sensor networks. IEEE-ACM Transactions on Networking (2004)
Lu, G., Krishnamachari, B., Cauligi, Raghavendra, S.: An adaptive energy-efficient and low-latency mac for data gathering in sensor networks. In: International workshop on Alghoritms for Wireless, Mobile, ad Hoc Sensor Networks (WMAN 2004) (2004)
Hoesel, V., Chatterjea, H.: An energy efficient medium access protocol for wireless sensor networks. In: ProRISC 2003 (2003)
Bieszczad, A., Pagurek, B., White, T.: Mobile agents for network management. IEEE Communications Surveys 1 (1998)
Haque, N., Jennings, N.R., Moreau, L.: Resource allocation in communication networks using market-based agents. International Journal of Knowledge Based Systems (2005)
Wang, Y., Cuthbert, L., Bigham, J.: Intelligent radio resource management for ieee 802.11 wlan. In: IEEE Wireless Communications and Networking Conference (WCNC), Atlanta, Georgia, USA (2004)
Kevin Mayer, K.T., Ellis, K.: Cattle health monitoring using wireless sensor networks. In: The 2nd IASTED International Conference on Communication and Computer Networks, Cambridge, Massachusetts, pp. 8–10 (2004)
Ruzzelli, A., Tynan, R., O’Hare, G.M.P.: A low-latency routing protocol for wireless sensor networks. In: SENET 2005 Advanced Industrial Conference on Wireless Technologies, Montreal (to appear, 2005)
Rao, A.S., Georgeff, M.: Modelling rational agents within a bdi architecture. In: Principles of Knowledge Representation and Reasoning, San Mateo, CA (1991)
O’Hare, G.M.P.: Agent Factory: An Environment for the Fabrication of Multi-Agent Systems. In: Foundations of Distributed Artificial Intelligence. John Wiley and Sons, Chichester (1996)
Collier, R., O’Hare, G.M.P., Lowen, T., Rooney, C.: Beyond prototyping in the valley of the agents. In: Mařík, V., Müller, J.P., Pěchouček, M. (eds.) CEEMAS 2003. LNCS, vol. 2691, p. 383. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ruzzelli, A.G., O’Grady, M.J., O’Hare, G.M.P., Tynan, R. (2006). Adaptive Scheduling in Wireless Sensor Networks. In: Stavrakakis, I., Smirnov, M. (eds) Autonomic Communication. WAC 2005. Lecture Notes in Computer Science, vol 3854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11687818_22
Download citation
DOI: https://doi.org/10.1007/11687818_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32992-3
Online ISBN: 978-3-540-32993-0
eBook Packages: Computer ScienceComputer Science (R0)