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TAGPP: a tiny aggregation algorithm with preprocessing in local cluster
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DOI：10.1109/NSWCTC.2009.122.png)
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Abstract
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hundreds or thousands of sensor nodes are deployed to WSNs (wireless sensor networks). They contribute to collect data in various environment, but with limited battery power. There are some deficiencies in WSNs. Many sensors share limited wireless channel bandwidth, which leads to some sensors lose their data sent to cluster-head Many cheap sensors are equipped to nodes for low cost and they usually have poor capability of sensing. They are easy to be interfered by harsh environment they work, leading to measurement error and noise disturbance For these deficiencies, a tiny data aggregation algorithm with preprocessing applied to individual local cluster, based on Grubbs criteria, fuzzy clustering, is proposed in the paper. Clustering is also adopted, as an important mechanism, to reduce energy consumption and make better network performance. Individual cluster sensors' data can be aggregated in cluster-head and Just the accurate result sent to sink node The simulation results show that It can efficiently eliminate outlier (abnormal data), make up for the impact of missing data in communications and improve data preciseness.
Keywords:
wireless sensor networks
data fusion
outlier
grubbs criteria
fuzzy clustering
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