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Network Slicing
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Network Slicing

A special issue of Network (ISSN 2673-8732).

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 15303

Special Issue Editors

Dr. Bin Han

E-Mail Website
Guest Editor
Division of Wireless Communication and Radio Positioning, University of Kaiserslautern, Kaiserslautern, Germany
Interests: 5G/B5G/6G networks; timely and reliable communication; multi-access edge computing; network slicing; non-stationary signal processing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Simon Pietro Romano

E-Mail Website
Guest Editor
Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Naples, Italy
Interests: networking; network security; real-time multimedia applications; standardization; network orchestration
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Patrick Seeling

E-Mail Website
Guest Editor
Department of Computer Science, Central Michigan University, Mount Pleasant, MI 48859, USA
Interests: beyond 5G networking; tactile internet; communication networks (mobile, multimedia, software-defined); computer-mediated education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Network slicing, as the most significant enabling technology of the 5G era, allows multiple logical networks (network slices) to share the same telecommunication network infrastructure. It brings to 5G networks enhancements in flexibility, resource efficiency, and security; and thereby identifies 5G with a capability of specialization with respect to highly heterogeneous service types. Empowered by network slicing, 5G systems are capable of fulfilling the extreme performance requirements of emerging use scenarios such as ultra-reliable low-latency communications (URLLC), and create novel business paradigms such as Slice-as-a-Service (SlaaS).

Shifting from the classical one-size-fits-all network topology for mixed data traffic to use-case-dependent network slice specification, from the layer-by-layer hierarchical designing approach to the cross-layer design towards end-to-end performance, the deployment of network slicing fundamentally changes the way we design, construct, operate, and manage mobile networks. Thereby, it raises technical challenges in all perspectives related to networking, including architectural design, technical enablers, business issues, optimization methods, and security concerns. In this Special Issue we solicit original papers in areas including but not limited to:

  • Architectural design of network slicing for industrial verticals;
  • End-to-end network slicing;
  • Energy efficiency of sliced networks;
  • Machine learning and artificial intelligence for network slicing;
  • Network slicing framework for the integration of terrestrial and non-terrestrial networks;
  • Network slicing with heterogeneous radio access technologies;
  • New business models in network slicing;
  • Privacy and security in network slicing;
  • Resource provisioning, orchestration, and management for network slicing;
  • Service-level agreement design for sliced networks;
  • Sliced network operation and management;
  • Technologies of software-defined networks and network function virtualization.

This is a joint special issue with Electronics.

Dr. Bin Han
Prof. Dr. Simon Pietro Romano
Prof. Dr. Patrick Seeling
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Network is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • network slicing
  • cross-layer design
  • E2E
  • heterogeneous networks
  • network function virtualization

Published Papers (5 papers)

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21 pages, 4367 KiB  
Article
NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations
by Gia Khanh Tran, Masanori Ozasa and Jin Nakazato
Network 2022, 2(4), 479-499; https://doi.org/10.3390/network2040029 - 26 Sep 2022
Cited by 9 | Viewed by 2011
Abstract
In the event of a major disaster, base stations in the disaster area will cease to function, making it impossible to obtain life-saving information. Therefore, it is necessary to provide a wireless communication infrastructure as soon as possible. To cope with this situation, [...] Read more.
In the event of a major disaster, base stations in the disaster area will cease to function, making it impossible to obtain life-saving information. Therefore, it is necessary to provide a wireless communication infrastructure as soon as possible. To cope with this situation, we focus on NFV/SDN (Network Function Virtualization/Software-Defined Networking)-enabled UAVs equipped with a wireless communication infrastructure to provide services. The access link between the UAV and the user is assumed to be equipped with a millimeter-wave interface to achieve high throughput. However, the use of millimeter-waves increases the effect of attenuation, making the deployment of UAVs problematic. In addition, if multiple UAVs are deployed in a limited frequency band, co-channel interference will occur between the UAVs, resulting in a decrease in the data rate. Therefore, in this paper, we propose a method that combines UAV placement and frequency division for a non-uniform user distribution in an environment with multiple UAVs. As a result, it is found that the offered data rate is improved by using our specific placement method, in terms of not only the average but also the outage user rate. Full article
(This article belongs to the Special Issue Network Slicing)
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19 pages, 2330 KiB  
Article
A Deep Contextual Bandit-Based End-to-End Slice Provisioning Approach for Efficient Allocation of 5G Network Resources
by Ralph Voltaire J. Dayot, In-Ho Ra and Hyung-Jin Kim
Network 2022, 2(3), 370-388; https://doi.org/10.3390/network2030023 - 23 Jun 2022
Viewed by 1761
Abstract
5G networks have been experiencing challenges in handling the heterogeneity and influx of user requests brought upon by the constant emergence of various services. As such, network slicing is considered one of the critical technologies for improving the performance of 5G networks. This [...] Read more.
5G networks have been experiencing challenges in handling the heterogeneity and influx of user requests brought upon by the constant emergence of various services. As such, network slicing is considered one of the critical technologies for improving the performance of 5G networks. This technology has shown great potential for enhancing network scalability and dynamic service provisioning through the effective allocation of network resources. This paper presents a Deep Reinforcement Learning-based network slicing scheme to improve resource allocation in 5G networks. First, a Contextual Bandit model for the network slicing process is created, and then a Deep Reinforcement Learning-based network slicing agent (NSA) is developed. The agent’s goal is to maximize every action’s reward by considering the current network state and resource utilization. Additionally, we utilize network theory concepts and methods for node selection, ranking, and mapping. Extensive simulation has been performed to show that the proposed scheme can achieve higher action rewards, resource efficiency, and network throughput compared to other algorithms. Full article
(This article belongs to the Special Issue Network Slicing)
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15 pages, 459 KiB  
Article
5G Network Slice Isolation
by Stan Wong, Bin Han and Hans D. Schotten
Network 2022, 2(1), 153-167; https://doi.org/10.3390/network2010011 - 08 Mar 2022
Cited by 5 | Viewed by 3821
Abstract
This article reveals an adequate comprehension of basic defense, security challenges, and attack vectors in deploying multi-network slicing. Network slicing is a revolutionary concept of providing mobile network on-demand and expanding mobile networking business and services to a new era. The new business [...] Read more.
This article reveals an adequate comprehension of basic defense, security challenges, and attack vectors in deploying multi-network slicing. Network slicing is a revolutionary concept of providing mobile network on-demand and expanding mobile networking business and services to a new era. The new business paradigm and service opportunities are encouraging vertical industries to join and develop their own mobile network capabilities for enhanced performances that are coherent with their applications. However, a number of security concerns are also raised in this new era. In this article, we focus on the deployment of multi-network slicing with multi-tenancy. We identify the security concerns and discuss the defense approaches such as network slice isolation and insulation in a multi-layer network slicing security model. Furthermore, we identify the importance to appropriately select the network slice isolation points and propose a generic framework to optimize the isolation policy regarding the implementation cost while guaranteeing the security and performance requirements. Full article
(This article belongs to the Special Issue Network Slicing)
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24 pages, 1266 KiB  
Article
Mobility- and Energy-Aware Cooperative Edge Offloading for Dependent Computation Tasks
by Mahshid Mehrabi, Shiwei Shen, Yilun Hai, Vincent Latzko, George P. Koudouridis, Xavier Gelabert, Martin Reisslein and Frank H. P. Fitzek
Network 2021, 1(2), 191-214; https://doi.org/10.3390/network1020012 - 04 Sep 2021
Cited by 15 | Viewed by 3791
Abstract
Cooperative edge offloading to nearby end devices via Device-to-Device (D2D) links in edge networks with sliced computing resources has mainly been studied for end devices (helper nodes) that are stationary (or follow predetermined mobility paths) and for independent computation tasks. However, end devices [...] Read more.
Cooperative edge offloading to nearby end devices via Device-to-Device (D2D) links in edge networks with sliced computing resources has mainly been studied for end devices (helper nodes) that are stationary (or follow predetermined mobility paths) and for independent computation tasks. However, end devices are often mobile, and a given application request commonly requires a set of dependent computation tasks. We formulate a novel model for the cooperative edge offloading of dependent computation tasks to mobile helper nodes. We model the task dependencies with a general task dependency graph. Our model employs the state-of-the-art deep-learning-based PECNet mobility model and offloads a task only when the sojourn time in the coverage area of a helper node or Multi-access Edge Computing (MEC) server is sufficiently long. We formulate the minimization problem for the consumed battery energy for task execution, task data transmission, and waiting for offloaded task results on end devices. We convert the resulting non-convex mixed integer nonlinear programming problem into an equivalent quadratically constrained quadratic programming (QCQP) problem, which we solve via a novel Energy-Efficient Task Offloading (EETO) algorithm. The numerical evaluations indicate that the EETO approach consistently reduces the battery energy consumption across a wide range of task complexities and task completion deadlines and can thus extend the battery lifetimes of mobile devices operating with sliced edge computing resources. Full article
(This article belongs to the Special Issue Network Slicing)
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37 pages, 13547 KiB  
Tutorial
Coexistence of Railway and Road Services by Sharing Telecommunication Infrastructure Using SDN-Based Slicing: A Tutorial
by Radheshyam Singh, José Soler, Tidiane Sylla, Leo Mendiboure and Marion Berbineau
Network 2022, 2(4), 670-706; https://doi.org/10.3390/network2040038 - 01 Dec 2022
Cited by 1 | Viewed by 2290
Abstract
This paper provides a detailed tutorial to develop a sandbox to emulate coexistence scenarios for road and railway services in terms of sharing telecommunication infrastructure using software-defined network (SDN) capabilities. This paper provides detailed instructions for the creation of network topology using Mininet–WiFi [...] Read more.
This paper provides a detailed tutorial to develop a sandbox to emulate coexistence scenarios for road and railway services in terms of sharing telecommunication infrastructure using software-defined network (SDN) capabilities. This paper provides detailed instructions for the creation of network topology using Mininet–WiFi that can mimic real-life coexistence scenarios between railways and roads. The network elements are programmed and controlled by the ONOS SDN controller. The developed SDN application can differentiate the data traffic from railways and roads. Data traffic differentiation is carried out using a VLAN tagging mechanism. Further, it also provides comprehensive information about the different tools that are used to generate the data traffic that can emulate messaging, video streaming, and critical data transmission of railway and road domains. It also provides the steps to use SUMO to represent the selected coexistence scenarios in a graphical way. Full article
(This article belongs to the Special Issue Network Slicing)
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