NDLI: A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities

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A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities

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A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities

Content Provider	ACM Digital Library
Author	Hefferman, Gerald Yang, Qing Tang, Bo Wei, Tao He, Haibo Chen, Zhen
Abstract	The ubiquitous deployment of various kinds of sensors in smart cities requires a new computing paradigm to support Internet of Things (IoT) services and applications, and big data analysis. Fog Computing, which extends Cloud Computing to the edge of network, fits this need. In this paper, we present 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 build large-scale, geospatial sensing networks, perform big data analysis, identify anomalous and hazardous events, and offer optimal responses in real-time. 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.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450337359
DOI	10.1145/2818869.2818898
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Fog computing Big data analysis Distributed computing architecture Pipeline safety monitoring Smart city
Content Type	Text
Resource Type	Article

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