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Wireless Sensor Networks for Big Data Systems.
Kim, Beom-Su; Kim, Ki-Il; Shah, Babar; Chow, Francis; Kim, Kyong Hoon.
Afiliação
  • Kim BS; Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Korea. bumsou10@naver.com.
  • Kim KI; Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Korea. kikim@cnu.ac.kr.
  • Shah B; College of Technological Innovation, Zayed University, Abu Dhabi 144534, UAE. babar.shah@zu.ac.ae.
  • Chow F; University College, Zayed University, Abu Dhabi 144534, UAE. Francis.Chow@zu.ac.ae.
  • Kim KH; Department of Informatics, Gyeongsang National University, Jinju 52828, Korea. khkim@gnu.ac.kr.
Sensors (Basel) ; 19(7)2019 Apr 01.
Article em En | MEDLINE | ID: mdl-30939722
ABSTRACT
Before discovering meaningful knowledge from big data systems, it is first necessary to build a data-gathering infrastructure. Among many feasible data sources, wireless sensor networks (WSNs) are rich big data sources a large amount of data is generated by various sensor nodes in large-scale networks. However, unlike typical wireless networks, WSNs have serious deficiencies in terms of data reliability and communication owing to the limited capabilities of the nodes. Moreover, a considerable amount of sensed data are of no interest, meaningless, and redundant when a large number of sensor nodes is densely deployed. Many studies address the existing problems and propose methods to overcome the limitations when constructing big data systems with WSN. However, a published paper that provides deep insight into this research area remains lacking. To address this gap in the literature, we present a comprehensive survey that investigates state-of-the-art research work on introducing WSN in big data systems. Potential applications and technical challenges of networks and infrastructure are presented and explained in accordance with the research areas and objectives. Finally, open issues are presented to discuss promising directions for further research.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article