A Fog computing-based efficient data management smart home architecture

Kelvin N. Lawal*, Titus K. Olaniyi, Ryan M. Gibson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Smart home technology comprises of multiple devices communicating with each other and human occupants to provide state of the art living conditions. The increased use of smart devices in smart homes, increases the rate of energy consumption. Among the plethora of smart devices within a smart home, one of the key smart devices that account for high data volume and rate of data transmission is the Closed-Circuit Television (CCTV) surveillance system. Furthermore, there has been multiple attempts by researchers to use Cloud computing solution to address the issue of storage and processing capabilities. However, the use of Cloud computing has challenges such as energy consumption, latency, and network bandwidth usage bottlenecks with energy cost set to increase by April 2022. The introduction of Fog computing as a solution aim to address existing Cloud computing issues such as energy consumption, latency, and network bandwidth usage, providing improvements to mobility, security and on demand requests. In this paper, Fog computing will provide a method that supports the management of data generated by CCTV camera system while reducing the energy consumption, latency, and network bandwidth usage. The work presented in this paper demonstrates efficiency and optimisation of energy consumption, latency, and network bandwidth usage using iFogSim2 network simulation toolkit. A comparison and interpretation of results from the iFogSim2 output for Cloud and Fog based scenarios is used to evaluate improvements in energy consumption, latency, and network bandwidth usage demonstrating the benefits of Fog based scenario to efficiently manage data from the CCTV camera system.
Original languageEnglish
Title of host publicationProceedings of the Future Technologies Conference (FTC) 2022, Volume 2
EditorsKohei Arai
PublisherSpringer
Pages233–257
Number of pages25
Volume2
ISBN (Electronic)9783031184581
ISBN (Print)9783031184574
DOIs
Publication statusE-pub ahead of print - 13 Oct 2022

Publication series

NameLecture Notes in Networks and Systems
Volume560
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Keywords

  • Fog computing
  • Cloud computing
  • Data management
  • Internet of Things
  • Smart home

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Computer Networks and Communications

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