Abstract
Wireless sensor network (WSN) has been paid more attention by scholars due to the practical communication of a system of devices to transfer information gathered from a monitored field through wireless links. Precise and accurate data of aggregating messages from sensor nodes is a vital demand for a success WSN application. This paper proposes a new scheme of identifying the correctness data scheme for aggregating data in cluster heads in hierarchical WSN based on naive Bayes classification. The collecting environmental information includes temperature, humidity, sound, and pollution levels, from sensor nodes to cluster heads that classify data fault and aggregate and transfer them to the base station. The collecting data is classified based on the classifier to aggregate in the cluster head of WSN. Compared with some existing methods, the proposed method offers an effective way of forwarding the correct data in WSN applications.
Highlights
Wireless sensor network (WSN) refers to a set of spatially dispersed and dedicated sensors for recording and monitoring the physical conditions and organizing the data collected at a central location [1, 2]
This paper considers the correct data to transfer from cluster head (CH) to the base station (BS) of WSN
5 Conclusion In this paper, a new scheme of collecting data classification for aggregating data in cluster heads (CHs) in hierarchical WSN based on the naive Bayes approach was presented
Summary
Wireless sensor network (WSN) refers to a set of spatially dispersed and dedicated sensors for recording and monitoring the physical conditions and organizing the data collected at a central location [1, 2]. WSNs are a low-cost network that is widely used in numerous applications [3,4,5]. The needed environmental information like temperature, light, sound, humidity, wind, air, and water pollution levels could be captured and measured by sensor nodes of WSN [6,7,8,9]. A good designed and employed WSN often follows the clustering fashion as efficient ways of saving energy networks that is to generate clusters by arranging the sensor nodes into groups [10].
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