A Data Processing Algorithm in EPC Internet of Things

With the rapid growth of data which sensed by the sensor nodes deployed in the logistics center, the current data processing methods have been impossible to meet the requirements of rapid and efficient analysis and processing for big data. In order to satisfy the demand, this paper designs a data pr...

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Published in2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery pp. 128 - 131
Main Authors Huiqun Zhao, Chuancong Huang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
Online AccessGet full text
DOI10.1109/CyberC.2014.30

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Abstract With the rapid growth of data which sensed by the sensor nodes deployed in the logistics center, the current data processing methods have been impossible to meet the requirements of rapid and efficient analysis and processing for big data. In order to satisfy the demand, this paper designs a data processing algorithm which is implemented by Hadoop. The experimental results show that our method can greatly improve the system efficiency of data processing.
AbstractList With the rapid growth of data which sensed by the sensor nodes deployed in the logistics center, the current data processing methods have been impossible to meet the requirements of rapid and efficient analysis and processing for big data. In order to satisfy the demand, this paper designs a data processing algorithm which is implemented by Hadoop. The experimental results show that our method can greatly improve the system efficiency of data processing.
Author Chuancong Huang
Huiqun Zhao
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Snippet With the rapid growth of data which sensed by the sensor nodes deployed in the logistics center, the current data processing methods have been impossible to...
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StartPage 128
SubjectTerms Algorithm design and analysis
Cloud computing
Data analysis
data processing algorithm
Filtering algorithms
hadoop
Internet of Things
Logistics
logistics center
MapReduce
Title A Data Processing Algorithm in EPC Internet of Things
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