Identifying correctness data scheme for aggregating data in cluster heads of wireless sensor network based on naive Bayes classification

Shu-Chuan Chu, Thi-Kien Dao, Jeng-Shyang Pan, Trong-The Nguyen

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Article number52
JournalEURASIP Journal on Wireless Communications and Networking
Volume2020
Issue number1
Early online date27 Feb 2020
DOIs
Publication statusPublished - 2020
Externally publishedYes

Bibliographical note

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. © The Authors. 2020.

Keywords

  • Wireless sensor network
  • Naive Bayes
  • Fault detection
  • Classification

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