Abstract
Future generation intelligent systems will harvest embedded intelligence as a means of delivering new and innovative services in diverse domains. Amongst the most challenging scenarios are those that consist of Wireless Sensor Networks (WSNs) as their functional operating constraints are significant. This paper proposes the use of in-network data aggregation techniques to enable the efficient acquisition of data in a water quality forecasting WSN application. Such an approach reduces the energy required for data transmission by collecting statistics from the network rather than analyzing the raw data centrally. Specifically, clustering points, where aggregation occurs, are modelled as mobile intelligent agents.
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References
Chave, P.: The EU Water Framework Directive: An Introduction. IWA Publishing (2001)
Dennett, D.: Brainstorms. The MIT Press (1981)
Duman, H., Hagras, H., Callaghan, V.: Intelligent association selection of embedded agents in intelligent inhabited environments. Pervasive and Mobile Computing 3(2), 117–157 (2007)
Fuqiang, Y.: The research on distributed data stream mining based on mobile agent. Procedia Engineering 23(0), 103–108 (2011)
Haddadi, A.: Reasoning about cooperation in agent systems: A pragmatic Theory. Ph.D. thesis, UMIST (1995)
Handcock, R.N., Swain, D.L., Bishop-Hurley, G.J., Patison, K.P., Wark, T., Valencia, P., Corke, P., O’Neill, C.J.: Monitoring animal behaviour and environmental interactions using wireless sensor networks, gps collars and satellite remote sensing. Sensors 9(5), 3586–3603 (2009)
Lowen, T.D., O’Hare, G.M.P., O’Hare, P.T.: Mobile agents point the way: context sensitive service delivery through mobile lightweight agents. In: Proceedings of the First International Joint Conference on Autonomous agents and Multiagent Systems: Part 2, AAMAS 2002, pp. 664–665. ACM, New York (2002)
Mo, L., He, Y., Liu, Y., Zhao, J., Tang, S.J., Li, X.Y., Dai, G.: Canopy closure estimates with greenorbs: sustainable sensing in the forest. In: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys 2009, pp. 99–112. ACM, New York (2009)
Muldoon, C., O’Hare, G.M.P., O’Grady, M.J., Tynan, R.: Agent migration and communication in wsns. In: Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2008, pp. 425–430. IEEE (2008)
Muldoon, C., O’Hare, G.M.P., Collier, R.W., O’Grady, M.J.: Towards pervasive intelligence: Reflections on the evolution of the agent factory framework. In: El Fallah Seghrouchni, A., Dix, J., Dastani, M., Bordini, R.H. (eds.) Multi-Agent Programming, pp. 187–212. Springer US (2009)
O’Grady, M.J., O’Hare, G.M.P., Chen, J., Phelan, D.: Distributed network intelligence: A prerequisite for adaptive and personalised service delivery. Information Systems Frontiers 11, 61–73 (2009)
O’Hare, G.M.P., O’Grady, M.J., Keegan, S., O’Kane, D., Tynan, R., Marsh, D.: Intelligent agile agents: Active enablers for ambient intelligence. In: ACM’s Special Interest Group on Computer-Human Interaction (SIGCHI), Ambient Intelligence for Scientific Discovery (AISD) Workshop, Vienna, Austria, April 25 (2004)
O’Hare, G.M.P., O’Grady, M.J., Muldoon, C., Bradley, J.F.: Embedded agents: a paradigm for mobile services. International Journal of Web and Grid Services 2(4), 379–405 (2006)
O’Hare, G.M.P., O’Grady, M.J., Tynan, R., Muldoon, C., Kolar, H., Ruzzelli, A., Diamond, D., Sweeney, E.: Embedding intelligent decision making within complex dynamic environments. Artificial Intelligence Review 27, 189–201 (2007)
Ramanathan, N., Balzano, L., Estrin, D., Hansen, M., Harmon, T., Jay, J., Kaiser, W., Sukhatme, G.: Designing wireless sensor networks as a shared resource for sustainable development. In: International Conference on Information and Communication Technologies and Development (ICTD 2006), pp. 256–265 (May 2006)
Shen, S., O’Hare, G.M.P., O’Grady, M.J.: Fuzzy-set-based decision making through energy-aware and utility agents within wireless sensor networks. Artificial Intelligence Review 27, 165–187 (2007)
Wark, T., Corke, P., Sikka, P., Klingbeil, L., Guo, Y., Crossman, C., Valencia, P., Swain, D., Bishop-Hurley, G.: Transforming agriculture through pervasive wireless sensor networks. IEEE Pervasive Computing 6(2), 50–57 (2007)
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Garcia, M.S. et al. (2012). An Agent-Based Wireless Sensor Network for Water Quality Data Collection. In: Bravo, J., López-de-Ipiña, D., Moya, F. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2012. Lecture Notes in Computer Science, vol 7656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35377-2_63
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DOI: https://doi.org/10.1007/978-3-642-35377-2_63
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