Chapter
Sep 21, 2015
IOT Big Data Process Based on Context Temporal-Spatial Characteristics in Petroleum Products Distribution
Authors: Min Li, Shaoquan Ni, Ling Zhou, and Qiang HuangAuthor Affiliations
Publication: ICTE 2015
Abstract
For solving problem of heterogeneity data process and low data processing capability in IOT, data in IOT is abstracted as “Context”; taking “Context” as the unified object in IOT big data process, a model of big data process based on Hadoop framework (HDC) is designed. Finally, apply the proposed model to solve problem of vehicle scheduling in petroleum products distribution, capacity of data process is validated by MapReduce distributed parallel computing experiments. Results of the experiments show that HDC has obvious excellence in big data process compared with ordinary computing system.
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Published In
ICTE 2015
Pages: 2065 - 2074
Copyright
© 2015 American Society of Civil Engineers.
History
Published online: Sep 21, 2015
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Authors
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Min Li
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China.
2National Railway Train Diagram Research and Training Center, Southwest Jiaotong University, Chengdu 610031, China.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China.
School of Distance and Continuing Education, Southwest Jiaotong University, Chengdu 610031, China.
Shaoquan Ni
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China.
2National Railway Train Diagram Research and Training Center, Southwest Jiaotong University, Chengdu 610031, China.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China.
Ling Zhou
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China.
Qiang Huang
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China.
2National Railway Train Diagram Research and Training Center, Southwest Jiaotong University, Chengdu 610031, China.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China.
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