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Softwarization of mobile network functions towards agile and energy efficient 5G architectures: a survey

  • Future mobile networks (MNs) are required to be flexible with minimal infrastructure complexity, unlike current ones that rely on proprietary network elements to offer their services. Moreover, they are expected to make use of renewable energy to decrease their carbon footprint and of virtualization technologies for improved adaptability and flexibility, thus resulting in green and self-organized systems. In this article, we discuss the application of software defined networking (SDN) and network function virtualization (NFV) technologies towards softwarization of the mobile network functions, taking into account different architectural proposals. In addition, we elaborate on whether mobile edge computing (MEC), a new architectural concept that uses NFV techniques, can enhance communication in 5G cellular networks, reducing latency due to its proximity deployment. Besides discussing existing techniques, expounding their pros and cons and comparing state-of-the-art architecturalFuture mobile networks (MNs) are required to be flexible with minimal infrastructure complexity, unlike current ones that rely on proprietary network elements to offer their services. Moreover, they are expected to make use of renewable energy to decrease their carbon footprint and of virtualization technologies for improved adaptability and flexibility, thus resulting in green and self-organized systems. In this article, we discuss the application of software defined networking (SDN) and network function virtualization (NFV) technologies towards softwarization of the mobile network functions, taking into account different architectural proposals. In addition, we elaborate on whether mobile edge computing (MEC), a new architectural concept that uses NFV techniques, can enhance communication in 5G cellular networks, reducing latency due to its proximity deployment. Besides discussing existing techniques, expounding their pros and cons and comparing state-of-the-art architectural proposals, we examine the role of machine learning and data mining tools, analyzing their use within fully SDN- and NFV-enabled mobile systems. Finally, we outline the challenges and the open issues related to evolved packet core (EPC) and MEC architectures.show moreshow less

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Metadaten
Author:Thembelihle DlaminiORCiDGND, Michele Rossi, Daniele Munaretto
URN:urn:nbn:de:bvb:384-opus4-1174320
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/117432
ISSN:1530-8669OPAC
ISSN:1530-8677OPAC
Parent Title (English):Wireless Communications and Mobile Computing
Publisher:Hindawi Limited
Place of publication:London
Type:Article
Language:English
Year of first Publication:2017
Publishing Institution:Universität Augsburg
Release Date:2024/12/10
Volume:2017
First Page:8618364
DOI:https://doi.org/10.1155/2017/8618364
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik / Professur für Quantencomputing und Quantengeräte
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Licence (German):License LogoCC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)