Abstract
Data prediction has been emerged as an important way to reduce the number of transmissions in wireless sensor networks(WSNs). This paper proposes a periodic data prediction algorithm called P-DPA in WSNs. The P-DPA takes the potential law hidden in periodicity as a reference to adjust the data prediction, which helps to improve the accuracy of prediction algorithm. The experiments of temperature, humidity and light intensity based on the dataset which comes from the actual data collected from 54 sensors deployed in the Intel Berkeley Research lab proved that the P-DPA has an obvious enhancement to the existing data prediction algorithms.
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Zhao, J., Liu, H., Li, Z., Li, W. (2013). Periodic Data Prediction Algorithm in Wireless Sensor Networks. In: Wang, R., Xiao, F. (eds) Advances in Wireless Sensor Networks. CWSN 2012. Communications in Computer and Information Science, vol 334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36252-1_65
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DOI: https://doi.org/10.1007/978-3-642-36252-1_65
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