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Future Internet
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Network Architectures and Protocols for Edge Learning in B5G IoT...
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Network Architectures and Protocols for Edge Learning in B5G IoT Systems

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 1925

Special Issue Editors

Dr. Latif Ladid

E-Mail Website
Guest Editor
Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg
Interests: IPv6; IoT; 5G; SDN-NFV
Special Issues, Collections and Topics in MDPI journals
Dr. Muslim Elkotob

E-Mail Website
Guest Editor
Vodafone, 40549 Düsseldorf, Germany
Interests: SDN/NFV; autonomics; slicing and security in 5G and IoT
Prof. Dr. Tayeb BenMeriem

E-Mail Website
Guest Editor
Vice-Chair, IPv6 Forum, 06152 Valbonne, France
Interests: 5G; IPv6; broadband; metaverse; AI; blockchain; autonomous networking

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of the current state of the art in Future Internet technologies, focusing on Edge Learning methods and applications, as well as the evolution of the classical Edge into a Smart Edge that is capable of reasoning and decision-making. We encourage contributions that convey how Edge leverages learning and AI to enhance its capabilities and take on a more significant role in the end-to-end Beyond 5G value chain. We invite research articles that will consolidate our understanding in this area, cover the aforementioned topics, and embody the concepts in theory and practice (simulations, PoCs, and test versions). This Special Issue will publish full research papers and reviews. Potential topics include, but are not limited to, the following research areas:

  • Network architectures;
  • Network optimization;
  • Network protocols;
  • Interconnected networks;
  • Edge learning;
  • AI-enhanced and AI-capable Edge;
  • Edge computing;
  • Smart Edge;
  • Fog computing

  • New Internet Protocol IPv6

  • Blockchain
  • Net5.5G.

Dr. Latif Ladid
Dr. Muslim Elkotob
Prof. Dr. Tayeb BenMeriem
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. Future Internet is an international peer-reviewed open access monthly 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 1600 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 architectures
  • network protocols
  • edge learning
  • 5G

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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22 pages, 1158 KiB  
Article
FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
by Bruno Ramos-Cruz, Francisco J. Quesada-Real, Javier Andreu-Pérez and Jessica Zaqueros-Martinez
Future Internet 2025, 17(7), 295; https://doi.org/10.3390/fi17070295 - 30 Jun 2025
Viewed by 201
Abstract
In the rapidly evolving landscape of the Internet of Things (IoT), managing the vast volumes of data generated by connected devices presents significant challenges, particularly in B5G IoT environments. One key issue is data redundancy, where identical data is stored several times because [...] Read more.
In the rapidly evolving landscape of the Internet of Things (IoT), managing the vast volumes of data generated by connected devices presents significant challenges, particularly in B5G IoT environments. One key issue is data redundancy, where identical data is stored several times because it is captured by multiple sensors. To address this, we introduce “FODIT”, a filter-based module designed to optimize data storage in IoT systems. FODIT leverages probabilistic data structures, specifically filters, to improve storage efficiency and query performance. We hypothesize that applying these structures can significantly reduce redundancy and accelerate data access in resource-constrained IoT deployments. We validate our hypothesis through targeted simulations under a specific and rare configuration: high-frequency and high-redundancy environments, with controlled duplication rates between 4% and 8%. These experiments involve data storage in local databases, cloud-based systems, and distributed ledger technologies (DLTs). The results demonstrate FODIT’s ability to reduce storage requirements and improve query responsiveness under these stress-test conditions. Furthermore, the proposed approach has broader applicability, particularly in DLT-based environments such as blockchain, where efficient querying remains a critical challenge. Nonetheless, some limitations remain, especially regarding the current data structure used to maintain consistency with the DLT, and the need for further adaptation to real-world contexts with dynamic workloads. This research highlights the potential of filter-based techniques to improve data management in IoT and blockchain systems, contributing to the development of more scalable and responsive infrastructures. Full article
(This article belongs to the Special Issue Network Architectures and Protocols for Edge Learning in B5G IoT Systems)
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Review

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19 pages, 1823 KiB  
Review
A Bibliometric Analysis and Visualization of In-Vehicle Communication Protocols
by Iftikhar Hussain, Manuel J. C. S. Reis, Carlos Serôdio and Frederico Branco
Future Internet 2025, 17(6), 268; https://doi.org/10.3390/fi17060268 - 19 Jun 2025
Viewed by 760
Abstract
This research examined the domain of intelligent transportation systems (ITS) by analyzing the impact of scholarly work and thematic prevalence, as well as focusing attention on vehicles, their technologies, cybersecurity, and related scholarly technologies. This was performed by examining the scientific literature indexed [...] Read more.
This research examined the domain of intelligent transportation systems (ITS) by analyzing the impact of scholarly work and thematic prevalence, as well as focusing attention on vehicles, their technologies, cybersecurity, and related scholarly technologies. This was performed by examining the scientific literature indexed in the Scopus database. This study analysed 2919 documents published between 2018 and 2025. The findings indicated that the highest and most significant journal was derived from IEEE Transactions on Vehicular Technology, with significant standing to the growth of communication and computing on vehicles with edge computing and AI optimization of vehicular systems. In addition, important PST research conferences highlighted the growing interest in academic research in cybersecurity for vehicle networks. Sensor networks, pose forensics, and privacy-preserving communication frameworks were some of the significant contributing fields marking the significance of the interdisciplinary nature of this research. Employing bibliometric analysis, the literature illustrated the multiple channels integrating knowledge creation and innovation in ITS through citation analysis. The outcome suggested an increasingly sophisticated research area, weighing technical progress and increasing concern about security and privacy measures. Further studies must investigate edge computing integrated with AI, advanced privacy-preserving linguistic protocols, and new vehicular network intrusion detection systems. Full article
(This article belongs to the Special Issue Network Architectures and Protocols for Edge Learning in B5G IoT Systems)
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