FOG-engine: Towards Big Data Analytics in the

被引：29
|
作者：
Mehdipour, Farhad [1 ,2 ]
Javadi, Bahman [3 ]
Mahanti, Aniket [4 ]
机构：
[1] Tech Futures Lab, Auckland, New Zealand
[2] Unitec Inst Technol, Auckland, New Zealand
[3] Univ Western Sydney, Sydney, NSW, Australia
[4] Univ Auckland, Auckland, New Zealand
来源：
2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC | 2016年
关键词：
Cloud computing; Fog computing; Internet of Things; Big data; Data analytics;
D O I：
10.1109/DASC-PICom-DataCom-CyberSciTec.2016.116
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Existing platforms fall short in providing effective solutions for big data analytics while the demands for processing large quantities of data in real-time are increasing. Moving data analytics towards where the data is generated and stored could be a solution for addressing this issue. In this paper, we propose a solution referred as FOG-engine, which is integrated into IoTs near the ground and facilitates data analytics before offloading large amounts of data to a central location. In this work, we introduce a model for data analytic using FOG-engines and discuss our plan for evaluating its efficacy in terms of several performance metrics such as processing speed, network bandwidth, and data transfer size.
引用
收藏
页码：640 / 646
页数：7
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