Handover decision with multi-access edge computing in 6G networks: A survey

Multi-Access Edge Computing (MEC) is a key technology in the evolution of mobile networks, especially for fifth and sixth generation (5G and 6G). MEC optimises communication and computational resources by hosting application processes close to the user equipment (UE) at the network edge, improving c...

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Main Authors: Saeid Jahandar, Ibraheem Shayea, Emre Gures, Ayman A. El-Saleh, Mustafa Ergen, Mohammad Alnakhli
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025000222
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author Saeid Jahandar
Ibraheem Shayea
Emre Gures
Ayman A. El-Saleh
Mustafa Ergen
Mohammad Alnakhli
author_facet Saeid Jahandar
Ibraheem Shayea
Emre Gures
Ayman A. El-Saleh
Mustafa Ergen
Mohammad Alnakhli
author_sort Saeid Jahandar
collection DOAJ
description Multi-Access Edge Computing (MEC) is a key technology in the evolution of mobile networks, especially for fifth and sixth generation (5G and 6G). MEC optimises communication and computational resources by hosting application processes close to the user equipment (UE) at the network edge, improving communication reliability and stability while reducing latency. A key feature of MEC is its ultra-low latency response, enabling real-time applications in next-generation networks. However, the mobility of UEs and the limited coverage of edge servers can lead to frequent handovers during the offloading process. As a result, advanced handover management strategies are required to jointly optimise handover and computation offloading. This paper provides a comprehensive overview of handover decision making in MEC systems, with particular emphasis on the challenges and solutions associated with the integration of communication, computation and mobility management. We examine the current state of research, provide an analysis of existing studies, and identify key gaps in the literature. The novelty of this work lies in its holistic approach to exploring the interdependencies between handover management, mobility control and computation offloading, while proposing future research directions. This work provides a forward-looking perspective on how these interrelated issues are likely to evolve, particularly in the context of future mobile networks using MEC technology.
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spelling doaj-art-a62bb770adf14c9ab94cfce6a8b8926c2025-01-24T04:45:36ZengElsevierResults in Engineering2590-12302025-03-0125103934Handover decision with multi-access edge computing in 6G networks: A surveySaeid Jahandar0Ibraheem Shayea1Emre Gures2Ayman A. El-Saleh3Mustafa Ergen4Mohammad Alnakhli5Computer Networks and Communication Systems, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, GermanyElectronics and Communication Engineering Department, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), 34467 Istanbul, Turkey; Corresponding author.Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic; Corresponding author.College of Engineering, A'Sharqiyah University (ASU), Ibra 400, Oman; Corresponding author.Electronics and Communication Engineering Department, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), 34467 Istanbul, TurkeyElectrical Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, 11991, Wadi Addwasir, Saudi ArabiaMulti-Access Edge Computing (MEC) is a key technology in the evolution of mobile networks, especially for fifth and sixth generation (5G and 6G). MEC optimises communication and computational resources by hosting application processes close to the user equipment (UE) at the network edge, improving communication reliability and stability while reducing latency. A key feature of MEC is its ultra-low latency response, enabling real-time applications in next-generation networks. However, the mobility of UEs and the limited coverage of edge servers can lead to frequent handovers during the offloading process. As a result, advanced handover management strategies are required to jointly optimise handover and computation offloading. This paper provides a comprehensive overview of handover decision making in MEC systems, with particular emphasis on the challenges and solutions associated with the integration of communication, computation and mobility management. We examine the current state of research, provide an analysis of existing studies, and identify key gaps in the literature. The novelty of this work lies in its holistic approach to exploring the interdependencies between handover management, mobility control and computation offloading, while proposing future research directions. This work provides a forward-looking perspective on how these interrelated issues are likely to evolve, particularly in the context of future mobile networks using MEC technology.http://www.sciencedirect.com/science/article/pii/S2590123025000222Sixth generation (6G)Fifth generation (5G)Multi-access edge computing (MEC)HandoverMobility management
spellingShingle Saeid Jahandar
Ibraheem Shayea
Emre Gures
Ayman A. El-Saleh
Mustafa Ergen
Mohammad Alnakhli
Handover decision with multi-access edge computing in 6G networks: A survey
Results in Engineering
Sixth generation (6G)
Fifth generation (5G)
Multi-access edge computing (MEC)
Handover
Mobility management
title Handover decision with multi-access edge computing in 6G networks: A survey
title_full Handover decision with multi-access edge computing in 6G networks: A survey
title_fullStr Handover decision with multi-access edge computing in 6G networks: A survey
title_full_unstemmed Handover decision with multi-access edge computing in 6G networks: A survey
title_short Handover decision with multi-access edge computing in 6G networks: A survey
title_sort handover decision with multi access edge computing in 6g networks a survey
topic Sixth generation (6G)
Fifth generation (5G)
Multi-access edge computing (MEC)
Handover
Mobility management
url http://www.sciencedirect.com/science/article/pii/S2590123025000222
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