IoT enabled Smart Fog Computing for Vehicular Traffic Control

INTRODUCTION: Internet was initially designed to connect web sites and portals with data packets flowing over the networks for communications at corporate levels. Over time, live video streaming, real-time data and voice is being offered over hosted Clouds for business entertainment. Enterprise appl...

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Main Authors: Akashdeep Bhardwaj, Sam Goundar
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2019-01-01
Series:EAI Endorsed Transactions on Internet of Things
Subjects:
iot
Online Access:https://eudl.eu/pdf/10.4108/eai.31-10-2018.162221
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spelling doaj-7248a820402b4dbf9cac43a92859fb902020-11-25T02:23:44ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Internet of Things2414-13992019-01-0151710.4108/eai.31-10-2018.162221IoT enabled Smart Fog Computing for Vehicular Traffic ControlAkashdeep Bhardwaj0Sam Goundar1University of Petroleum and Energy Studies, Dehradun, IndiaThe University of South Pacific, Suva, Fiji INTRODUCTION: Internet was initially designed to connect web sites and portals with data packets flowing over the networks for communications at corporate levels. Over time, live video streaming, real-time data and voice is being offered over hosted Clouds for business entertainment. Enterprise applications like Office 365, banking and e-commerce areavailable over smartphones. With the advent of Fog Computing and Internet of Things, corporate enterprises and non-IT industries see potential in this technology. Billions of Internet-enabled devices, globally distributed nodes, embedded sensorgateways transmit real-time generated over the internet to the cloud data centres. Cloud environments are not designed to handle this level of data that is being generated and Computing limits are being severely tested. Fog Computing has the potential to be the go-to option for Cloud service delivery.OBJECTIVES: This paper reviewed existing research works and presents unique Smart Fog Computing based taxonomy. The authors also implemented experimental setup for Smart Cities using Smart Fog Computing for controlling Vehicular traffic.METHODS: Smart Vehicular Management is viable use case for Fog and IoT technology. The authors designed and implemented two experimental setups. The first setup involvesstandard Cloud implementation and the second setup employs Fog Computing implemented using IoT Sensor nodes to compare the performance of the Vehicle Management Fog application regarding the Response time and Bandwidth Consumed. The architecture and implementation involved deploying 50 IoT sensors nodes across the university areas and routes.RESULTS: The main results obtained in this paper are the following. As compared to Cloud computing, on deploying Fog Computing and IoT devices:<ul><li> End-to-End Processing time dropped from 29.44 to 6.7 seconds</li> <li> almost 77% less </li><li> Number of hops traversed reduced from 56 to 4 hops </li><li> almost 92% less </li><li> Bandwidth usage dropped from 247 to 8 kbps </li><li> almost 96.7% less </li>CONCLUSION: From the experimental setups as compared to Cloud computing, the Fog and IoT processes the traffic data locally on the edge devices, which reduces the end-to-end time.https://eudl.eu/pdf/10.4108/eai.31-10-2018.162221fog computingedge computinginternet of thingsfog securitycloudletsiot
collection DOAJ
language English
format Article
sources DOAJ
author Akashdeep Bhardwaj
Sam Goundar
spellingShingle Akashdeep Bhardwaj
Sam Goundar
IoT enabled Smart Fog Computing for Vehicular Traffic Control
EAI Endorsed Transactions on Internet of Things
fog computing
edge computing
internet of things
fog security
cloudlets
iot
author_facet Akashdeep Bhardwaj
Sam Goundar
author_sort Akashdeep Bhardwaj
title IoT enabled Smart Fog Computing for Vehicular Traffic Control
title_short IoT enabled Smart Fog Computing for Vehicular Traffic Control
title_full IoT enabled Smart Fog Computing for Vehicular Traffic Control
title_fullStr IoT enabled Smart Fog Computing for Vehicular Traffic Control
title_full_unstemmed IoT enabled Smart Fog Computing for Vehicular Traffic Control
title_sort iot enabled smart fog computing for vehicular traffic control
publisher European Alliance for Innovation (EAI)
series EAI Endorsed Transactions on Internet of Things
issn 2414-1399
publishDate 2019-01-01
description INTRODUCTION: Internet was initially designed to connect web sites and portals with data packets flowing over the networks for communications at corporate levels. Over time, live video streaming, real-time data and voice is being offered over hosted Clouds for business entertainment. Enterprise applications like Office 365, banking and e-commerce areavailable over smartphones. With the advent of Fog Computing and Internet of Things, corporate enterprises and non-IT industries see potential in this technology. Billions of Internet-enabled devices, globally distributed nodes, embedded sensorgateways transmit real-time generated over the internet to the cloud data centres. Cloud environments are not designed to handle this level of data that is being generated and Computing limits are being severely tested. Fog Computing has the potential to be the go-to option for Cloud service delivery.OBJECTIVES: This paper reviewed existing research works and presents unique Smart Fog Computing based taxonomy. The authors also implemented experimental setup for Smart Cities using Smart Fog Computing for controlling Vehicular traffic.METHODS: Smart Vehicular Management is viable use case for Fog and IoT technology. The authors designed and implemented two experimental setups. The first setup involvesstandard Cloud implementation and the second setup employs Fog Computing implemented using IoT Sensor nodes to compare the performance of the Vehicle Management Fog application regarding the Response time and Bandwidth Consumed. The architecture and implementation involved deploying 50 IoT sensors nodes across the university areas and routes.RESULTS: The main results obtained in this paper are the following. As compared to Cloud computing, on deploying Fog Computing and IoT devices:<ul><li> End-to-End Processing time dropped from 29.44 to 6.7 seconds</li> <li> almost 77% less </li><li> Number of hops traversed reduced from 56 to 4 hops </li><li> almost 92% less </li><li> Bandwidth usage dropped from 247 to 8 kbps </li><li> almost 96.7% less </li>CONCLUSION: From the experimental setups as compared to Cloud computing, the Fog and IoT processes the traffic data locally on the edge devices, which reduces the end-to-end time.
topic fog computing
edge computing
internet of things
fog security
cloudlets
iot
url https://eudl.eu/pdf/10.4108/eai.31-10-2018.162221
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