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Advanced Intelligent Systems Based on Internet of Things for 6G...
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Advanced Intelligent Systems Based on Internet of Things for 6G Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 1506

Special Issue Editors

Dr. Ali Khoshkholghi

E-Mail Website
Guest Editor
Department of Computer Science, Middlesex University London, London NW4 4BT, UK
Interests: cloud/edge computing; IoT; edge intelligence; 5G/6G; network security; NFV/SDN; network optimization
Prof. Dr. Javid Taheri

E-Mail Website
Guest Editor
Department of Computer Science, Karlstad University, 651 88 Karlstad, Sweden
Interests: cloud computing; edge computing; optimization; artificial intelligence; high-performance computing
Special Issues, Collections and Topics in MDPI journals
Dr. Andreas Johnsson

E-Mail Website
Guest Editor
Department of Information Technology, Uppsala University, 752 36 Uppsala, Sweden
Interests: network management; network measurement; machine learning; network performance; IoT

Special Issue Information

Dear Colleagues

The Internet of Things (IoT) has the potential to play a significant role in creating more advanced systems in various applications and industries such as smart cities and homes, cloud/edge computing, 5G/6G, healthcare, smart manufacturing, environment monitoring, retail, agriculture, etc. Integrating artificial intelligence and data analytics, IoT presents opportunities to enhance these systems towards advanced intelligent systems (AIS), revolutionizing various industries by providing improvements in efficiency and reducing costs. AIS leverage AI algorithms to make sense of vast amount of data generated by IoT devices, enabling optimization, automation, and smart decision-making. However, there are still many open challenges in this area to be explored, especially in the context of future mobile networks and their use cases.

This Special Issue aims to showcase research articles that contribute significant advancements in applying IoT and AI techniques in different use cases of the next generation of mobile networks (6G); 6G technology is still in its early stages of research and development, and the actual implementation and capabilities may evolve over time. However, the potential for IoT applications in 6G networks is vast, promising to bring about transformative changes across various industries and aspects of daily life.

This Special Issue welcomes submissions investigating IoT’s benefits and applications in 6G networks while addressing the challenges of current applications and systems such as energy efficacy, security and privacy, interoperability, reliability, data management, connectivity, etc. The topics of interest for this Special Issue include, but are not limited to, the application of AI, IoT and data analytics for:

  • Massive IoT connectivity
  • Ubiquitous sensing
  • Holographic communications
  • Tactile Internet
  • AI-driven autonomous systems
  • Smart infrastructure
  • Enhanced wearables
  • Supply chain and logistics
  • Remote education and training
  • Agriculture and environment
  • Wildlife conservation
  • Entertainment and media

Dr. Ali Khoshkholghi
Prof. Dr. Javid Taheri
Dr. Andreas Johnsson
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. Electronics 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.

Keywords

  • Internet of Things
  • artificial intelligence
  • security and privacy for intelligent systems
  • cloud/edge computing
  • federated learning
  • big data analytics

Published Papers (2 papers)

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Research

18 pages, 832 KiB  
Article
On the Secrecy Sum-Rate of Internet of Things Networks: Scheduling and Power Control
by Inkyu Bang, Seong Ho Chae and Bang Chul Jung
Electronics 2024, 13(11), 2074; https://doi.org/10.3390/electronics13112074 - 27 May 2024
Viewed by 357
Abstract
Physical-layer security (PLS) has attracted much attention in wireless communications and has been considered one of the main candidates for enhancing wireless security in future 6G networks. Recent studies in the PLS area have focused on investigating and analyzing the characteristics of secure [...] Read more.
Physical-layer security (PLS) has attracted much attention in wireless communications and has been considered one of the main candidates for enhancing wireless security in future 6G networks. Recent studies in the PLS area have focused on investigating and analyzing the characteristics of secure transmissions in multiuser networks (e.g., the massive number of Internet of Things (IoT) devices in 6G networks). Due to the difficulty of obtaining the exact secrecy capacity region in wireless multiuser networks, several alternative methods are used to characterize the secrecy performance of multiuser networks. For example, we can analyze the secrecy sum-rate scaling in terms of the number of users based on multiuser diversity (MUD). In this paper, we propose an opportunistic user scheduling scheme that achieves optimal MUD gain, combined with a power control mechanism for reducing information leakage to multiple eavesdroppers in wireless networks. The proposed scheme considers multiuser transmissions in one scheduling time slot by adopting orthogonal random beamforming at the receiver to exploit the full degrees-of-freedom gain with an assumption that each user (or IoT device) is equipped with a single antenna, and base station and eavesdroppers have multiple antennas. The main contribution of this paper is to derive the analytic result of the achievable secrecy sum-rate scaling in a high signal-to-noise ratio (SNR) regime. We evaluate the performance of the proposed scheduling scheme with a power control mechanism through simulations with both internal and external eavesdropping scenarios. We further discuss the extensibility of our analysis to various applications such as satellite communications and IoT networks. Full article
(This article belongs to the Special Issue Advanced Intelligent Systems Based on Internet of Things for 6G Networks)
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16 pages, 3142 KiB  
Article
A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory
by Issam Al-Nader, Aboubaker Lasebae, Rand Raheem and Ali Khoshkholghi
Electronics 2023, 12(23), 4766; https://doi.org/10.3390/electronics12234766 - 24 Nov 2023
Cited by 2 | Viewed by 835
Abstract
The multiple objective optimisation (MOO) challenges encountered in the context of wireless sensor networks (WSNs) present a formidable NP-hard problem. These issues primarily arise from the constraints imposed by critical factors such as connectivity, coverage, and, most notably, energy consumption. Simultaneously fulfilling these [...] Read more.
The multiple objective optimisation (MOO) challenges encountered in the context of wireless sensor networks (WSNs) present a formidable NP-hard problem. These issues primarily arise from the constraints imposed by critical factors such as connectivity, coverage, and, most notably, energy consumption. Simultaneously fulfilling these three requirements is no longer considered the standard approach for enhancing system dependability. To illustrate, a prospective solution may optimise one or two of these requirements while bolstering overall network energy efficiency. Nonetheless, prior endeavours documented in the extant literature reveal unexplored avenues for enhancement. Hence, this paper introduces a new methodology aimed at alleviating MOO concerns and thereby enhancing the quality of service (QoS) in WSNs. A long short-term memory (LSTM) model is proposed as an analytical tool to deliver an energy-efficient scheduling solution that aligns and optimises WSN parameters, striving to attain the most favourable system performance. The LSTM algorithm’s effectiveness is assessed through the iterative application of periods, confirming the desired QoS levels. The unique feature of LSTM lies in its capability to observe specific event sequences and subsequently establish them as the system’s default configuration for its entire operational lifespan. Once these favourable parameters are identified, LSTM automatically ensures consistent service availability and reliability throughout the network’s lifespan. The results obtained demonstrate the superiority of the proposed LSTM-based scheduling algorithm in comparison to the self-organising map (SOFM)-based node scheduling algorithm. The LSTM-based approach outperforms the SOFM-based alternative by a remarkable 75% in terms of coverage and exhibits a 20% enhancement in network lifetime, all while maintaining equivalent levels of connectivity (i.e., 99%) in both algorithms. Full article
(This article belongs to the Special Issue Advanced Intelligent Systems Based on Internet of Things for 6G Networks)
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