Abstract
Energy is one of the most important resources in wireless sensor networks (WSN). Due to unattended nature of WSNs, it should be used smartly and efficiently to maximize lifetime. A map representing the residual energy of sensor nodes in the sensor field can be constructed, which is called as energy map. Depletion of energy in sensor nodes can be modeled as time-series. The grey models are considered to be the best tool for time–series prediction. In this paper, we propose a grey system theory-based prediction approach to construct the energy map for WSN. Simulation results show that our proposed approach outperforms various prediction based approaches for energy map construction.
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References
Kay, R., Mattern, F.: The Design Space of Wireless Sensor Networks. IEEE Wireless Communications 11(6), 54–61 (2004)
Haenselmann, T.: Sensornetworks. GFDL Wireless Sensor Network textbook, http://pi4.informatik.uni-mannheim.de/~haensel/sn_book (retrieved August 29, 2006)
Tiwari, A., Ballal, P., Lewis, F.L.: Energy-efficient wireless sensor network design and implementation for condition-based maintenance. ACM Transactions on Sensor Networks (TOSN) 3(1) (2007)
Hadim, S., Mohamed, N.: Middleware: middleware challenges and approaches for wireless sensor networks. IEEE Distributed Systems Online 7(3), 1 (2006)
Katiyar, V., Chand, N., Chauhan, N.: Recent Advances and future trends in Wireless Sensor Networks. International Journal of Applied Engineering Research 2(1), 43–55 (2010)
Zhao, Y.J., Govindan, R., Estrin, D.: Residual Energy Scans for Monitoring Wireless Sensor Networks. In: IEEE Wireless Communications and Networking Conference, pp. 356–362 (2002)
Mini, A.F., Antonio, L.A.F., Nath, B.: The distinctive design characteristic of a wireless sensor network: the energy map. Computer Communications 27, 935–945 (2004)
Mini, R.A.F., Machado, M.V., Loureiro, A.A.F., Nath, B.: Prediction-based Energy map for Wireless Sensor Networks. Ad Hoc Net. J. 3, 235–253 (2005)
Song, C., Guizani, M.: Energy map: Mining Wireless Sensor Network Data. In: International Conference on Communications, 2006, ICC 2006, vol. 8, pp. 3525–3529. IEEE, Los Alamitos (2006)
Song, C., Guizani, M., Sharif, H.: Adaptive clustering in wireless sensor networks by mining sensor energy data. Computer Communications 30, 2968–2975 (2007)
Al-Karaki, J.N., Ghada, Al-Mashaqbeh, A.: Energy-centric routing in wireless sensor networks. Microprocessors and Microsystems 31, 252–262 (2007)
Niculescu, D., Nath, B.: Trajectory-based forwarding and its applications. In: Rutgers University Technical Report DCS-TR-488, pp. 1–18 (2002)
Goussevskaia, O., Machado, M.V., Mini, R.A.F., Loureiro, A.A.F., Mateus, G.R., Nogueira, J.M.: Data Dissemination Based on the Energy map. Topics in Ad-hoc Networking, IEEE Communications Magazine, 134–143 (2005)
Rhazi, A.E.L., Pierre, S.: A Data Collection Algorithm Using Energy maps in Sensor Networks. In: Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2007 (2007)
Kayacan, E., Ulutas, B., Kaynak, O.: Grey system theory-based models in time series prediction. Expert Systems with Applications 37, 1784–1789 (2010)
Deng, J.L.: Introduction to grey system theory. The Journal of Grey System 1(1), 1–24 (1989)
Han, S., Chan, E.: Continuous Residual Energy Monitoring in Wireless Sensor Networks. In: Cao, J., Yang, L.T., Guo, M., Lau, F. (eds.) ISPA 2004. LNCS, vol. 3358, pp. 169–177. Springer, Heidelberg (2004)
Li, M., Liu, Y.: Iso-Map: Energy-Efficient Contour Mapping in Wireless Sensor Networks. IEEE Transactions on Knowledge and Data Engineering 22(5), 699–710 (2010)
Reddy, A., Estrin, D., Govindan, R.: Large Scale Fault Isolation. IEEE Journal of Selected Areas in Communication, Special Issue on Network Management, 733–743 (2000)
Zhao, J., Govindan, R., Estrin, D.: Computing aggregates for monitoring wireless sensor networks. Technical Report 02-773, USC (September 2003)
Brockwell, P.J., Davis, R.A.: Introduction to Time Series and Forecasting, 2nd edn. Springer, New York (2002)
Box, G.E.P., Jenkins, G.M.: Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco (1976)
Mini, R.A.F., Loureiro, A.A.F., Nath, B.: Energy map Construction for Wireless Sensor Network under a Finite Energy Budget. In: MSWiM 2004, pp. 165–169 (2004)
Tenenbaum, J.B., Silva, V.D., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290, 2319–2323 (2000)
Wei, G., Linga, Y., Guoa, B., Xiaob, B., Vasilakos, A.V.: Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter. Computer Communication 34(6), 793–802 (2011)
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Katiyar, V., Chand, N., Soni, S. (2011). Grey System Theory-Based Energy Map Construction for Wireless Sensor Networks. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22720-2_12
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DOI: https://doi.org/10.1007/978-3-642-22720-2_12
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