Empowering the Internet of Things Using Light Communication and Distributed Edge Computing

With the rapid growth of connected devices, new issues emerge, which will be addressed by boosting capacity, improving energy efficiency, spectrum usage, and cost, besides offering improved scalability to handle the growing number of linked devices. This can be achieved by introducing new technologies to the traditional Internet of Things (IoT) networks. Visible light communication (VLC) is a promising technology that enables bidirectional transmission over the visible light spectrum achieving many benefits, including ultra-high data rate, ultra-low latency, high spectral efficiency, and ultra-high reliability. Light Fidelity (LiFi) is a form of VLC that represents an efficient solution for many IoT applications and use cases, including indoor and outdoor applications. Distributed edge computing is another technology that can assist communications in IoT networks and enable the dense deployment of IoT devices. To this end, this work considers designing a general framework for IoT networks using LiFi and a distributed edge computing scheme. It aims to enable dense deployment, increase reliability and availability, and reduce the communication latency of IoT networks. To meet the demands, the proposed architecture makes use of MEC and fog computing. For dense deployment situations, a proof-of-concept of the created model is presented. The LiFi-integrated fog-MEC model is tested in a variety of conditions, and the findings show that the model is efficient. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Authors
Ateya A.A. 1 , Mahmoud M.1 , Zaghloul A.1 , Soliman N.F.2 , Muthanna A. 3, 4
Publisher
MDPI AG
Number of issue
9
Language
English
Status
Published
Number
1511
Volume
11
Year
2022
Organizations
  • 1 Department of Electronics and Communications Engineering, Zagazig University, Zagazig, 44519, Egypt
  • 2 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
  • 3 Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, Saint Petersburg, 193232, Russian Federation
  • 4 Department of Applied Probability and Informatics, Peoples’ Friendship, University of Russia (RUDN University), Moscow, 117198, Russian Federation
Keywords
fog computing; internet of things; latency; light fidelity; multiple access edge computing
Date of creation
06.07.2022
Date of change
06.07.2022
Short link
https://repository.rudn.ru/en/records/article/record/83644/
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