Summary
The wireless sensor network is a wireless network consisting of spatially distributed autonomous sensor devices which are called sensor nodes in remote setting to cooperatively monitor and control physical or environmental conditions. The lifetimes of sensor nodes depend on the energy availability with energy consumption. Due to the size limitation and remoteness of sensor devices after deployment, it is not able to resupply or recharge power. The system energy saving effectiveness is the probability that the wireless sensor network system can successfully meet an energy saving operational demand. To extend the system effectiveness in energy saving, the lifetimes of sensor nodes must be increased by making them energy efficient as possible. In this paper, we propose Bayesian statistical models for observed active and sleep times data of sensor nodes under the selected energy efficient CSMA contention-based MAC protocols in consideration of the system effectiveness in energy saving in a wireless sensor network. Accordingly, we propose Bayes estimators for the system energy saving effectiveness of the wireless sensor networks by use of the Bayesian method under the conjugate prior information.
This work was supported by the Pukyong National University Research Fund in 2008 (PK-2008-028).
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References
Bharghavan, V., Demers, A., Shenker, S., Zhang, L.: MACAW: A Media Access Protocol for Wireless LAN’s. In: Proceedings of the ACM SIGCOMM Conference on Communications Architectures, Protocols and Applications, London, UK, 31 August- 2 September, pp. 212–225 (1994)
Demirkol, I., Ersoy, C., Alagöz, F.: MAC Protocols for Wireless Sensor Networks: A Survey. IEEE Communications Magazine 44(4), 115–121 (2006)
Halkes, G.P., van Dam, T., Langendoen, K.G.: Comparing energy-saving MAC protocols for wireless sensor networks. In: Mobile Networks and Applications, vol. 10(5), pp. 783–791. Kluwer Academic Publishers, Hingham (2005)
van Dam, T., Langendoen, K.: An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, Los Angeles, USA, pp. 171–180, November 5-7 (2003)
Polastre, J., Culler, D.: B-MAC: An Adaptive CSMA Layer for Low-Power Operation. Technical Report CS294-F03/BMAC, UC Berkeley (December 2003)
Sagduyu, Ephremides, Y.E.: The Problem of Medium Access Control in Wireless Sensor Networks. IEEE Wireless Communications 1(6), 44–53 (2004)
Dunkels, A., Österlind, F., Tsiftes, N., He, Z.: Software-based sensor node energy estimation. In: Proceedings of the 5th International Conference on Embedded Networked Sensor Systems, Sydney, Australia, November 6-9, 2007, pp. 409–410 (2007)
Stemm, M., Katz, R.H.: Measuring and Reducing Energy Consumption of Network Interfaces in Hand-held Devices. IEICE Transactions on Communications E80-B, 1125–1131 (1997)
Pourret, O., Naïm, P., Marcot, B.: Bayesian Networks: A Practical Guide to Applications. John Wiley & Sons Ltd., Chichester (2008)
Neil, M., Fenton, N.E., Tailor, M.: Using Bayesian Networks to model Expected and Unexpected Operational Losses. An International Journal of Risk Analysis 25(4), 963–972 (2005)
Murphy, K.P.: Dynamic Bayesian Networks: Representation, Inference and Learning. Ph.D. thesis, UC Berkeley, Computer Science Division (July 2002)
Stann, F., Heidemann, J.: BARD: Bayesian-Assisted Resource Discovery in Sensor Networks. In: Proceedings of the. 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2005), Miami, Florida, USA, March 13-17, 2005, vol. 2, pp. 866–877 (2005)
Martz, H.F., Waller, R.A.: Bayesian Reliability Analysis of Complex Series/Parallel Systems of Binomial Subsystems and Components. Technometrics 32(4), 407–416 (1990)
Gutierrez, J.A., Naeve, M., Callaway, E., Bourgeois, M., Mitter, V., Heile, B.: IEEE 802.15.4: A Developing Standard for Low-Power Low-Cost Wireless Personal Area Networks. IEEE Network 15(5), 12–19 (2001)
IEEE 802.15 WPANTM Task Group 4 (TG4), http://www.ieee802.org/15/pub/TG4.html (retrieved, 7th March, 2009)
Sandler, G.H.: System Reliability Engineering. Prentice-Hall, Englewood Cliffs (1963)
Pearl, J.: Bayesian Networks: A Model of Self-Activated Memory for Evidential Reasoning. In: Proceedings of the 7th Conference of the Cognitive Science Society, August 15-17, 1985, pp. 329–334. University of California, Irvine (1985)
Raiffa, H., Schlaifer, R.: Applied Statistical Decision Theory (1st edn. Harvard University Press, Cambridge, 1961), Paperback edn. John Wiley & Sons, Chichester (2000)
De Groot, M.H.: Optimal Statistical Decisions. McGraw-Hill, New York (1970)
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Kim, M.H., Park, MG. (2009). Bayesian Statistical Modeling of System Energy Saving Effectiveness for MAC Protocols of Wireless Sensor Networks. In: Lee, R., Ishii, N. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01203-7_20
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DOI: https://doi.org/10.1007/978-3-642-01203-7_20
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