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Outlier Detection Techniques for Wireless Sensor Networks: A Survey

Yang Zhang ; Meratnia, Nirvana ; Havinga, Paul

IEEE Communications surveys and tutorials, 2010-01, Vol.12 (2), p.159-170 [Periódico revisado por pares]

New York: IEEE

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  • Título:
    Outlier Detection Techniques for Wireless Sensor Networks: A Survey
  • Autor: Yang Zhang ; Meratnia, Nirvana ; Havinga, Paul
  • Assuntos: Acoustic noise ; Acoustic sensors ; Chemical sensors ; Defense industry ; Errors ; Event detection ; Guidelines ; Intelligent sensors ; Networks ; Noise ; Outlier ; outlier detection ; Sensors ; Tables (data) ; Taxonomy ; Temperature sensors ; Wireless sensor networks
  • É parte de: IEEE Communications surveys and tutorials, 2010-01, Vol.12 (2), p.159-170
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree.
  • Editor: New York: IEEE
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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