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Bayesian Statistical Modeling of System Energy Saving Effectiveness for MAC Protocols of Wireless Sensor Networks

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 209))

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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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01202-0

  • Online ISBN: 978-3-642-01203-7

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