Open Access

ARTICLE

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

by Abdelhamied A. Ateya¹, Amel Ali Alhussan^2,*, Hanaa A. Abdallah³, Mona A. Al duailij², Abdukodir Khakimov⁴, Ammar Muthanna⁵

1 Department of Electronics and Communications Engineering, Zagazig University, Zagazig, Sharqia, 44519, Egypt
2 Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
3 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 84428, Saudi Arabia
4 Department of Applied Probability and Informatics, Peoples’ Friendship University of Russia (RUDN University), Moscow, 117198, Russia
5 Center for Telecommunication Research, School of Postgraduate Studies & Research, Sri Lanka Technological Campus, Padukka, 10500, Sri Lanka

* Corresponding Author: Amel Ali Alhussan. Email:

Computer Systems Science and Engineering 2023, 45(2), 1775-1787. https://doi.org/10.32604/csse.2023.031841

Received 28 April 2022; Accepted 08 June 2022; Issue published 03 November 2022

Abstract

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, we propose a seamless migration technique for complex edge computing structures. The developed migration scheme enables services to adapt to the required load on the radio channels. The proposed algorithm is analyzed for various use cases, and a test bench has been developed to emulate the operator’s infrastructure. The obtained results are introduced and discussed.

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Keywords

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