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Author:

Mukhtar, M. (Mukhtar, M..) | Yunus, F. (Yunus, F..) | Li, J. (Li, J..) | Atta-ur-Rahman (Atta-ur-Rahman.) | Mahmood, T. (Mahmood, T..) | Ali, Y.A.A. (Ali, Y.A.A..)

Indexed by:

EI Scopus SCIE

Abstract:

Generally, mobility management (MM) solutions are centralized, which means only one entity controls the mobility-related tasks of mobile nodes connected to the network. However, the massive number of users, rapid growth in the network traffic, and the recent developments regarding the architecture and capability of 5G networks forced multiple entities to perform the task of MM. Similarly, to fulfill the demand for the applications at the time of handoff, we have on-demand MM solutions. These solutions are designed to be adoptable to various service delivery use cases supported by future networks. In addition, they also have power-saving features that turn them off automatically, when all your devices are fully charged. Owing to stated features, we need to explore on-demand MM solutions and these solutions can provide divergent types of services according to the user’s demand. Therefore, in this paper, the importance and comparison of on-demand MM solutions with legacy mechanisms are presented, by keeping in view the merits and constraints of their contributions. Furthermore, the significance of the MM as a service (MMaaS) model is discussed in detail, which is used for the on-demand MM mechanism. In this model, the substantial characteristics of the granularity of services are also elaborated, which are intricately tangled with the adoptability, extensibility, and power-saving requirements of future wireless networks. Finally, we discuss the challenges, future prospects, and application areas of on-demand MM solutions for researchers and application developers. Author

Keyword:

MM MMaaS Wireless networks Extensibility MN 5G Software Long Term Evolution Switches Beyond 5G Quality of service 5G mobile communication

Author Community:

  • [ 1 ] [Mukhtar M.]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Yunus F.]Department Ocean Engineering and Informatics, Universiti Malaysia Terengganu, TRG, Malaysia
  • [ 3 ] [Li J.]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] Atta-ur-Rahman, Department of Computer Science, Imam Abdulrahman bin Faisal University, Dammam, Saudi Arabia
  • [ 5 ] [Mahmood T.]Artificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh, Kingdom of Saudi Arabia
  • [ 6 ] [Ali Y.A.A.]Department of Information System, Faculty of Computer Science and Information System Najran University, Kingdom of Saudi Arabia

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Source :

IEEE Access

ISSN: 2169-3536

Year: 2023

Volume: 11

Page: 1-1

3 . 9 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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