Survey on Network Slicing for Internet of Things Realization in 5G Networks

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Title: Survey on Network Slicing for Internet of Things Realization in 5G Networks
Authors: Wijethilaka, ShalithaLiyanage, Madhusanka
Permanent link: http://hdl.handle.net/10197/12083
Date: 22-Mar-2021
Online since: 2021-04-12T16:27:07Z
Abstract: Internet of Things (IoT) is an emerging technology that makes people’s lives smart by conquering a plethora of diverse application and service areas. In near future, the fifth-generation (5G) wireless networks provide the connectivity for this IoT ecosystem. It has been carefully designed to facilitate the exponential growth in the IoT field. Network slicing is one of the key technologies in the 5G architecture that has the ability to divide the physical network into multiple logical networks (i.e. slices) with different network characteristics. Therefore, network slicing is also a key enabler of realisation of IoT in 5G. Network slicing can satisfy the various networking demands by heterogeneous IoT applications via dedicated slices. In this survey, we present a comprehensive analysis of the exploitation of network slicing in IoT realisation. We discuss network slicing utilisation in different IoT application scenarios, along with the technical challenges that can be solved via network slicing. Furthermore, integration challenges and open research problems related to the network slicing in the IoT realisation are also discussed in this paper. Finally, we discuss the role of other emerging technologies and concepts, such as blockchain and Artificial Intelligence/Machine Learning(AI/ML) in network slicing and IoT integration.
Funding Details: University College Dublin
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Communications Surveys & Tutorials
Start page: 1
End page: 1
Copyright (published version): 2021 IEEE
Keywords: Network slicingInternet of Things5G mobile communicationResource managementComputer architectureWireless sensor networksSoftware
DOI: 10.1109/comst.2021.3067807
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection

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