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Author:

Qureshi, Muhammad Mukhtar (Qureshi, Muhammad Mukhtar.) | Yunus, Farizah Binti (Yunus, Farizah Binti.) | Li, Jianqiang (Li, Jianqiang.) | Ur-Rahman, Atta (Ur-Rahman, Atta.) | Mahmood, Tariq (Mahmood, Tariq.) | Ali, Yahya Ali Abdelrahman (Ali, Yahya Ali Abdelrahman.)

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.

Keyword:

MM beyond 5G MMaaS MN 5G

Author Community:

  • [ 1 ] [Qureshi, Muhammad Mukhtar]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Qureshi, Muhammad Mukhtar]Univ Malaysia Terengganu, Fac Ocean Engn Technol & Informat, Kaula Nerus, Terengganu, Malaysia
  • [ 3 ] [Yunus, Farizah Binti]Univ Malaysia Terengganu, Fac Ocean Engn Technol & Informat, Kaula Nerus, Terengganu, Malaysia
  • [ 4 ] [Qureshi, Muhammad Mukhtar]Iqra Univ, Dept Comp & Technol, Chak Shahzad Campus, Islamabad 45550, Pakistan
  • [ 5 ] [Li, Jianqiang]Beijing Engn Res Ctr IoT Software & Syst, Beijing 100124, Peoples R China
  • [ 6 ] [Ur-Rahman, Atta]Imam Abdulrahman Bin Faisal Univ, Coll Comp Sci & Informat Technol, Dept Comp Sci, Dammam, Saudi Arabia
  • [ 7 ] [Mahmood, Tariq]CCIS Prince Sultan Univ, Artificial Intelligence & Data Analyt AIDA Lab, Riyadh 11586, Saudi Arabia
  • [ 8 ] [Mahmood, Tariq]Univ Educ, Fac Informat Sci, Vehari Campus, Vehari 61100, Pakistan
  • [ 9 ] [Ali, Yahya Ali Abdelrahman]Najran Univ, Fac Comp Sci & Informat Syst, Dept Informat Syst, Najran, Saudi Arabia

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Source :

IEEE ACCESS

ISSN: 2169-3536

Year: 2023

Volume: 11

Page: 114864-114879

3 . 9 0 0

JCR@2022

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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