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5G Enabled Energy Innovation
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5G Enabled Energy Innovation

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (28 May 2021) | Viewed by 19427

Special Issue Editor

Dr. Michael Alexandros Kourtis

E-Mail Website
Guest Editor
National Centre for Scientific Research ”DEMOKRITOS” (NCSRD), Institute of Informatics and Telecommunications, 153 10 Athens, Greece
Interests: NFV; SDN; 6G networks; network slicing; swarm intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The advent of 5G network communications, coupled with the proliferation of Cloud and IoT technologies, has created an urgent need to enhance cutting-edge wireless technology. Breakthroughs in the deployment, integration, security, slicing and operational range of wireless networking can provide new potential capabilities for the next decade, in the form of intelligent data centers investigating and analyzing energy processes. To realize this promise, however, various key enablers should be defined in the areas of artificial intelligence (AI), deep learning (DL), network virtualization, network slicing and intelligent sensors and devices. Leveraging advanced technologies, such as 5G, can enable new architectures that support a dynamic, near-realtime end-to-end fabric that predicts and responds to measurement conditions, thus dramatically improving the value of collected data. Furthermore, critical infrastructure must respond to a continuously evolving environment. Breakthroughs in wireless instrumentation architectures are required in order to provide dynamic, robust, reliable, and repeatable operations. 5G will play an important role not only in the wireless communication innovation, but also in the design and realization of an end-to-end chain of operations for heterogeneous and demanding environments. Innovation in the field of Energy should be based on the pillars of 5G technology, namely multi-connectivity, robustness, reliability, and adaptability. By harnessing next-generation networks we can design and build the infrastructure needed to understand and discover new scientific milestones in the field of Energy.

Dr. Michael Alexandros Kourtis
Guest Editor

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. Energies 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 2600 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

  • 5G
  • IoT
  • AI
  • DL
  • Network Slicing
  • Edge

Published Papers (6 papers)

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Research

15 pages, 2658 KiB  
Article
Conceptual Evaluation of a 5G Network Slicing Technique for Emergency Communications and Preliminary Estimate of Energy Trade-Off
by Michail-Alexandros Kourtis, Thanos Sarlas, Giorgios Xilouris, Michael C. Batistatos, Charilaos C. Zarakovitis, Ioannis P. Chochliouros and Harilaos Koumaras
Energies 2021, 14(21), 6876; https://0-doi-org.brum.beds.ac.uk/10.3390/en14216876 - 20 Oct 2021
Cited by 11 | Viewed by 2354
Abstract
The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially [...] Read more.
The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence of 5G network slicing in various areas of emergency vertical applications. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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14 pages, 782 KiB  
Article
Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures
by Ioannis P. Chochliouros, Michail-Alexandros Kourtis, Anastasia S. Spiliopoulou, Pavlos Lazaridis, Zaharias Zaharis, Charilaos Zarakovitis and Anastasios Kourtis
Energies 2021, 14(17), 5392; https://0-doi-org.brum.beds.ac.uk/10.3390/en14175392 - 30 Aug 2021
Cited by 28 | Viewed by 4785
Abstract
Energy efficiency is a huge opportunity for both the developed and the developing world, and ICT will be the key enabler towards realising this challenge, in a huge variety of ways across the full range of industries. In the telecommunications space in particular, [...] Read more.
Energy efficiency is a huge opportunity for both the developed and the developing world, and ICT will be the key enabler towards realising this challenge, in a huge variety of ways across the full range of industries. In the telecommunications space in particular, power consumption and the resulting energy-related pollution are becoming major operational and economical concerns. The exponential increases in network traffic and the number of connected devices both make energy efficiency an increasingly important concern for the mobile networks of the (near) future. More specifically, as 5G is being deployed at a time when energy efficiency appears as a significant matter for the network ability to take into account and to serve societal and environmental issues, this can play a major role in helping industries to achieve sustainability goals. Within this scope, energy efficiency has recently gained its own role as a performance measure and design constraint for 5G communication networks and this has identified new challenges for the future. In particular, the inclusion of AI/ML techniques will further enhance 5G’s capabilities to achieve lower power consumption and, most importantly, dynamic adaption of the network elements to any sort of energy requirements, to ensure effective functioning. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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15 pages, 1860 KiB  
Article
Quantum-Driven Energy-Efficiency Optimization for Next-Generation Communications Systems
by Su Fong Chien, Heng Siong Lim, Michail Alexandros Kourtis, Qiang Ni, Alessio Zappone and Charilaos C. Zarakovitis
Energies 2021, 14(14), 4090; https://0-doi-org.brum.beds.ac.uk/10.3390/en14144090 - 6 Jul 2021
Cited by 7 | Viewed by 2160
Abstract
The advent of deep-learning technology promises major leaps forward in addressing the ever-enduring problems of wireless resource control and optimization, and improving key network performances, such as energy efficiency, spectral efficiency, transmission latency, etc. Therefore, a common understanding for quantum deep-learning algorithms is [...] Read more.
The advent of deep-learning technology promises major leaps forward in addressing the ever-enduring problems of wireless resource control and optimization, and improving key network performances, such as energy efficiency, spectral efficiency, transmission latency, etc. Therefore, a common understanding for quantum deep-learning algorithms is that they exploit advantages of quantum hardware, enabling massive optimization speed ups, which cannot be achieved by using classical computer hardware. In this respect, this paper investigates the possibility of resolving the energy efficiency problem in wireless communications by developing a quantum neural network (QNN) algorithm of deep-learning that can be tested on a classical computer setting by using any popular numerical simulation tool, such as Python. The computed results show that our QNN algorithm can be indeed trainable and that it can lead to solution convergence during the training phase. We also show that the proposed QNN algorithm exhibits slightly faster convergence speed than its classical ANN counterpart, which was considered in our previous work. Finally, we conclude that our solution can accurately resolve the energy efficiency problem and that it can be extended to optimize other communications problems, such as the global optimal power control problem, with promising trainability and generalization ability. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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27 pages, 444 KiB  
Article
On the Design of IoT Security: Analysis of Software Vulnerabilities for Smart Grids
by Christos-Minas Mathas, Costas Vassilakis, Nicholas Kolokotronis, Charilaos C. Zarakovitis and Michail-Alexandros Kourtis
Energies 2021, 14(10), 2818; https://0-doi-org.brum.beds.ac.uk/10.3390/en14102818 - 14 May 2021
Cited by 12 | Viewed by 3579
Abstract
The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet of Things (IoT) will proliferate, and IoT devices will be included in many [...] Read more.
The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet of Things (IoT) will proliferate, and IoT devices will be included in many 5G application contexts, including the Smart Grid. Even though 5G technology has been designed by taking security into account, design provisions may be undermined by software-rooted vulnerabilities in IoT devices that allow threat actors to compromise the devices, demote confidentiality, integrity and availability, and even pose risks for the operation of the power grid critical infrastructures. In this paper, we assess the current state of the vulnerabilities in IoT software utilized in smart grid applications from a source code point of view. To that end, we identified and analyzed open-source software that is used in the power grid and the IoT domain that varies in characteristics and functionality, ranging from operating systems to communication protocols, allowing us to obtain a more complete view of the vulnerability landscape. The results of this study can be used in the domain of software development, to enhance the security of produced software, as well as in the domain of automated software testing, targeting improvements to vulnerability detection mechanisms, especially with a focus on the reduction of false positives. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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25 pages, 2965 KiB  
Article
SWIPT-Assisted Energy Efficiency Optimization in 5G/B5G Cooperative IoT Network
by Maliha Amjad, Omer Chughtai, Muhammad Naeem and Waleed Ejaz
Energies 2021, 14(9), 2515; https://0-doi-org.brum.beds.ac.uk/10.3390/en14092515 - 27 Apr 2021
Cited by 13 | Viewed by 1905
Abstract
Resource use in point-to-point and point-to-multipoint communication emerges with the tremendous growth in wireless communication technologies. One of the technologies is wireless power transfer which may be used to provide sufficient resources for energy-constrained networks. With the implication of cooperative communication in 5G/B5G [...] Read more.
Resource use in point-to-point and point-to-multipoint communication emerges with the tremendous growth in wireless communication technologies. One of the technologies is wireless power transfer which may be used to provide sufficient resources for energy-constrained networks. With the implication of cooperative communication in 5G/B5G and the Internet of Things (IoT), simultaneous wireless information and power transfer (SWIPT)-assisted energy efficiency and appropriate resource use become challenging tasks. In this paper, multiple IoT-enabled devices are deployed to cooperate with the source node through intermediate/relay nodes powered by radio-frequency (RF) energy. The relay forwards the desired information generated by the source node to the IoT devices with the fusion of decode/amplify processes and charges itself at the same time through energy harvesting technology. In this regard, a problem with throughput, energy efficiency, and joint throughput with user admission maximization is formulated while assuring the useful, practical network constraints, which contemplate the upper/lower bounds of power transmitted by the source node, channel condition, and energy harvesting. The formulated problem is a mixed-integer non-linear problem (MINLP). To solve the formulated problem, the rate of individual IoT-enabled devices (b/s), number of selected IoT devices, and the sum-rate maximization are prosecuted for no-cooperation, cooperation with diversity, and cooperation without diversity. Moreover, a comparison of the outer approximation algorithm (OAA) and mesh adaptive direct search algorithm (MADS) for non-linear optimization with the exhaustive search algorithm is provided. The results with reference to the complexity of the algorithms have also been evaluated which show that 4.68×10−10 OAA and 7.81×10−11 MADS as a percent of ESA, respectively. Numerous simulations are carried out to exhibit the usefulness of the analysis to achieve the convergence to ε-optimal solution. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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17 pages, 2697 KiB  
Article
5G-Enabled UAVs with Command and Control Software Component at the Edge for Supporting Energy Efficient Opportunistic Networks
by Harilaos Koumaras, George Makropoulos, Michael Batistatos, Stavros Kolometsos, Anastasios Gogos, George Xilouris, Athanasios Sarlas and Michail-Alexandros Kourtis
Energies 2021, 14(5), 1480; https://0-doi-org.brum.beds.ac.uk/10.3390/en14051480 - 8 Mar 2021
Cited by 31 | Viewed by 3724
Abstract
Recently Unmanned Aerial Vehicles (UAVs) have evolved considerably towards real world applications, going beyond entertaining activities and use. With the advent of Fifth Generation (5G) cellular networks and the number of UAVs to be increased significantly, it is created the opportunity for UAVs [...] Read more.
Recently Unmanned Aerial Vehicles (UAVs) have evolved considerably towards real world applications, going beyond entertaining activities and use. With the advent of Fifth Generation (5G) cellular networks and the number of UAVs to be increased significantly, it is created the opportunity for UAVs to participate in the realisation of 5G opportunistic networks by carrying 5G Base-Stations to under-served areas, allowing the provision of bandwidth demanding services, such as Ultra High Definition (UHD) video streaming, as well as other multimedia services. Among the various improvements that will drive this evolution of UAVs, energy efficiency is considered of primary importance since will prolong the flight time and will extend the mission territory. Although this problem has been studied in the literature as an offline resource optimisation problem, the diverse conditions of a real UAV flight does not allow any of the existing offline optimisation models to be applied in real flight conditions. To this end, this paper discusses the amalgamation of UAVs and 5G cellular networks as an auspicious solution for realising energy efficiency of UAVs by offloading at the edge of the network the Flight Control System (FCS), which will allow the optimisation of the UAV energy resources by processing in real time the flight data that have been collected by onboard sensors. By exploiting the Multi-access Edge Computing (MEC) architectural feature of 5G as a technology enabler for realising this offloading, the paper presents a proof-of-concept implementation of such a 5G-enabled UAV with softwarized FCS component at the edge of the 5G network (i.e., the MEC), allowing by this way the autonomous flight of the UAV over the 5G network by following control commands mandated by the FCS that has been deployed at the MEC. This proof-of-concept 5G-enabled UAV can support the execution of real-time resource optimisation techniques, a step-forward from the currently offline-ones, enabling in the future the execution of energy-efficient and advanced missions. Full article
(This article belongs to the Special Issue 5G Enabled Energy Innovation)
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