Incorporating Intelligence in Fog Computing for Big Data Analysis in Smart Cities

Data intensive analysis is the major challenge in smart cities because of the ubiquitous deployment of various kinds of sensors. The natural characteristic of geodistribution requires a new computing paradigm to offer location-awareness and latency-sensitive monitoring and intelligent control. Fog C...

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Bibliographic Details
Published inIEEE transactions on industrial informatics Vol. 13; no. 5; pp. 2140 - 2150
Main Authors Bo Tang, Zhen Chen, Hefferman, Gerald, Shuyi Pei, Tao Wei, Haibo He, Qing Yang
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Cloud computing
Computer architecture
Data analysis
Data management
Distributed computing
Edge computing
Feature extraction
fiber optic sensor
Fiber optics
fog computing
Intelligence
Intelligent sensors
Internet of Things (IoT)
Machine learning
Monitoring
Optical fibers
Pipeline safety
Sensors
Smart cities
smart pipeline
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Summary:Data intensive analysis is the major challenge in smart cities because of the ubiquitous deployment of various kinds of sensors. The natural characteristic of geodistribution requires a new computing paradigm to offer location-awareness and latency-sensitive monitoring and intelligent control. Fog Computing that extends the computing to the edge of network, fits this need. In this paper, we introduce a hierarchical distributed Fog Computing architecture to support the integration of massive number of infrastructure components and services in future smart cities. To secure future communities, it is necessary to integrate intelligence in our Fog Computing architecture, e.g., to perform data representation and feature extraction, to identify anomalous and hazardous events, and to offer optimal responses and controls. We analyze case studies using a smart pipeline monitoring system based on fiber optic sensors and sequential learning algorithms to detect events threatening pipeline safety. A working prototype was constructed to experimentally evaluate event detection performance of the recognition of 12 distinct events. These experimental results demonstrate the feasibility of the system's city-wide implementation in the future.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2017.2679740