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Intelligent Network Orchestration and Resource Management in 5G/6G Wireless Networks

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 22575

Special Issue Editors


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Guest Editor
Department of Informatics and Telecommunications, University of Peloponnese (UoP), GR-221 31 Tripoli, Greece
Interests: teletraffic engineering; performance evaluation and optimization of telecommunication networks; protocol analysis; network simulation; network planning; queueing theory
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute of Communication and Computer Networks, Faculty of Computing and Telecommunications, Poznan University of Technology, ul. Polanka 3, 60-965 Poznan, Poland
Interests: tele-traffic; performance evaluation; communications networks; switching and routing; traffic control; elastic optical switching networks
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical and Computer Engineering, University of Western Macedonia, 50100 Kozani, Greece
Interests: IoT; 5G mobile communication; UAV; quality of service; radio access networks; computer network security; radio networks; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Dept. of Electrical & Computer Engineering, University of Patras, Patras, Greece
Interests: teletraffic theory and engineering; traffic/network control; simulation and performance optimization of telecommunications networks

Special Issue Information

Dear Colleagues,

As advancements of 5G networks are maturing towards a global standard, the research community is gradually shifting its focus on the development of beyond 5G solutions, which are expected to support a wide variety of conflicting requirements. 6G networks will also introduce a range of new services relying on higher capacity, with peak throughput reaching a terabit per second (Tbps) and low latency below 1 ms, by leveraging the benefits of Artificial Intelligence and Big Data.

Emerging verticals, such as holographic communications, Augmented/Virtual (AR/VR) reality applications, Unmanned Aerial Vehicle (UAV) services, pervasive connectivity, distributed computing, and Internet of Everything will require very large volumes of data and time precision services in terms of latency and packet loss. These requirements call for a new architecture featuring large data volumes, high precision communications, satellite connectivity, and mobile edge computing technologies. A key feature in 6G networks is the network and data analytic services, enabled by the advancements in network softwarization and AI/ML technologies. By leveraging the edge cloud, analytics are expected to benefit all the aspects of a 6G network, such as the Radio Access Network, the core network, as well as the user applications and services.

The emerging 6G networks will explore new communication mechanisms, without being restricted by existing network paradigms, by leveraging new concepts, new architectures, new protocols, and new technologies. Although the benefits of network intelligence are immense, the realization of the intelligence in all network aspects poses several technical challenges, in contrast to traditional centralized artificial intelligence architectures. Therefore, it is crucial to identify these challenges and develop novel theoretical and applicable solutions.

The objective of this Special Issue is to bring together the state-of-the-art research contributions that address challenges in contemporary networks design, dimensioning and optimization towards the 6G networks. We are soliciting original contributions that have not been published and are not currently under consideration by any other journals.

The topics of primary interest include, but are not limited to:

  • Vision, key drivers, new services and requirements for 6G
  • System and network architectures for 5G/6G
  • 5G and beyond towards 6G testbeds and experimentation
  • Optical backhauling and hybrid architectures for 5G/6G
  • Intelligent radio access network architectures
  • Wireless Terahertz technologies
  • Spectrum modeling towards 6G
  • Next Generation IoT architectures
  • Distributed intelligence schemes
  • Grant-free transmission techniques in 6G-enabled IoT
  • Real-time industrial applications and services
  • Self-organizing 6G networks
  • Network softwarization
  • V2X communications
  • Cognitive automation
  • Predictive network orchestration and resource management methods
  • Security and privacy concepts
  • Blockchain-enabled security schemes

Prof. Dr. Ioannis D. Moscholios
Prof. Dr. Mariusz Głąbowski
Prof. Dr. Panagiotis Sarigiannidis
Dr. Thomas Lagkas
Prof. Michael D. Logothetis
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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.

Published Papers (3 papers)

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Research

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18 pages, 3081 KiB  
Article
Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic
by Iskanter-Alexandros Chousainov, Ioannis Moscholios, Panagiotis Sarigiannidis and Michael Logothetis
Appl. Sci. 2021, 11(18), 8559; https://doi.org/10.3390/app11188559 - 15 Sep 2021
Cited by 1 | Viewed by 1369
Abstract
In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units and are separated from the remote radio heads (RRHs). Based on their radio capacity, the RRHs may form one or many [...] Read more.
In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units and are separated from the remote radio heads (RRHs). Based on their radio capacity, the RRHs may form one or many clusters: a single cluster when all RRHs have the same capacity and multi-clusters where RRHs of the same radio capacity are grouped in the same cluster. Each RRH services the so-called multiservice traffic, i.e., calls from many service classes with various radio and computational resource requirements. Calls arrive in the RRHs according to a quasi-random process. This means that new calls are generated by a finite number of mobile users. Arriving calls require simultaneously computational and radio resource units in order to be accepted in the system, i.e., in the serving RRH. If their requirements are met, then these calls are served in the (serving) RRH for a service time which is generally distributed. Otherwise, call blocking occurs. We start with the single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time congestion probabilities via a convolution algorithm whose accuracy is validated with the aid of simulation. Furthermore, the previous model is generalized to include the more complex case of more than one clusters. Full article
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58 pages, 1886 KiB  
Article
From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey
by Mohammed Najah Mahdi, Abdul Rahim Ahmad, Qais Saif Qassim, Hayder Natiq, Mohammed Ahmed Subhi and Moamin Mahmoud
Appl. Sci. 2021, 11(17), 8117; https://doi.org/10.3390/app11178117 - 31 Aug 2021
Cited by 53 | Viewed by 16596
Abstract
Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard [...] Read more.
Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard. Full article
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Review

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23 pages, 560 KiB  
Review
Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review
by Doruk Sahinel, Simon Rommel and Idelfonso Tafur Monroy
Appl. Sci. 2022, 12(1), 221; https://doi.org/10.3390/app12010221 - 27 Dec 2021
Cited by 3 | Viewed by 3005
Abstract
Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable [...] Read more.
Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at the edge key resources similar to the available bandwidth in network communication channels. Aiming to understand the relationship between resource management, virtualization, and the dense 5G access and fronthaul with an emphasis on converged radio and optical communications, this article presents a review of how resource management solutions have dealt with optimizing millimeter wave radio and optical resources from an autonomic network management perspective. A research agenda is also proposed by identifying current state-of-the-art solutions and the need to shift all the convergent issues towards building an advanced resource management mechanism for beyond-5G. Full article
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