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Cluster Computing

Erschienen in:

25.08.2018

Flow data processing paradigm and its application in smart city using a cluster analysis approach

verfasst von: Xiang Zou, Jinghua Cao, Wei Sun, Quan Guo, Tao Wen

Erschienen in: Cluster Computing | Ausgabe 2/2019

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Abstract

In the digital revolution era the work style of the people changed into real and live communicative systems. Smart cities are evolved from the smart ecosystem with various domains like healthcare, information exchange, transportation, buildings etc., the presence of multiple information system makes these smart cities into a heterogeneous which includes multiple data transfer based on the large no of interconnected sub systems. Since the systems provide data from various terminals to the host the amount of information generates is same as the chances of increasing the challenges and issues in the smart city. These flow data from various sources are handled using cluster computing and this proposed research provides the data flow in the smart city using cluster computing. Apache spark is the tool used to handle the issues in the smart city which is much better than the Hadoop. The results discuss the comparison between the applications in same environment on both the tools.

Vorheriger Artikel A comparative study on spiking neural network encoding schema: implemented with cloud computing

Nächster Artikel Energy-aware RAID scheduling methods in distributed storage applications

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Titel: Flow data processing paradigm and its application in smart city using a cluster analysis approach
verfasst von: Xiang Zou
Jinghua Cao
Wei Sun
Quan Guo
Tao Wen
Publikationsdatum: 25.08.2018
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe 2/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-018-2839-y

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