Wireless IoT Network Protocols II

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 9394

Special Issue Editor


E-Mail Website
Guest Editor
DISUIT, University of Insubria, 2-21100 Varese, Italy
Interests: formal methods; timed probabilistic systems; hybrid system; cyber-physical systems; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the Internet of Things (IoT) paradigm, smart devices equipped with embedded technology automatically collect information from shared resources (e.g., Internet accesses, physical devices, etc.) and aggregates it to provide new services to end users. The “things” commonly deployed in IoT systems are RFID tags, for unique identification; sensors, to detect physical changes in the environment; and actuators, to pass on information to the environment. The range of IoT applications is rapidly increasing and already covers several domains, including environmental monitoring, healthcare, personal and social, security and surveillance, smart environments (home, offices, cities), transportation, and logistics (automotive). The practical development is driven by the evolution of the wireless networking technologies, which are facing a number of challenges.

The main aim of this Special Issue is to seek high-quality submissions focusing on theoretical and practical aspects of wireless IoT network protocols, including performance evaluation, simulation, and testbed.

Dr. Ruggero Lanotte
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. Information 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

  • internet of things wireless network protocols
  • models
  • performance evaluation
  • simulation

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

15 pages, 1706 KiB  
Article
A Flexible Infrastructure-Sharing 5G Network Architecture Based on Network Slicing and Roaming
by João P. Ferreira, Vinicius C. Ferreira, Sérgio L. Nogueira, João M. Faria and José A. Afonso
Information 2024, 15(4), 213; https://doi.org/10.3390/info15040213 - 10 Apr 2024
Viewed by 1206
Abstract
The sharing of mobile network infrastructure has become a key topic with the introduction of 5G due to the high costs of deploying such infrastructures, with neutral host models coupled with features such as network function virtualization (NFV) and network slicing emerging as [...] Read more.
The sharing of mobile network infrastructure has become a key topic with the introduction of 5G due to the high costs of deploying such infrastructures, with neutral host models coupled with features such as network function virtualization (NFV) and network slicing emerging as viable solutions for the challenges in this area. With this in mind, this work presents the design, implementation, and test of a flexible infrastructure-sharing 5G network architecture capable of providing services to any type of client, whether an operator or not. The proposed architecture leverages 5G’s network slicing for traffic isolation and compliance with the policies of different clients, with roaming employed for the authentication of users of operator clients. The proposed architecture was implemented and tested in a simulation environment using the UERANSIM and Open5GS open-source tools. Qualitative tests successfully validated the authentication and the traffic isolation features provided by the slices for the two types of clients. Results also demonstrate that the proposed architecture has a positive impact on the performance of the neutral host network infrastructure, achieving 61.8%-higher throughput and 96.8%-lower packet loss ratio (PLR) in a scenario sharing the infrastructure among four clients and eight users when compared to a single client with all the network resources. Full article
(This article belongs to the Special Issue Wireless IoT Network Protocols II)
Show Figures

Figure 1

29 pages, 4963 KiB  
Article
A Holistic Approach to Ransomware Classification: Leveraging Static and Dynamic Analysis with Visualization
by Bahaa Yamany, Mahmoud Said Elsayed, Anca D. Jurcut, Nashwa Abdelbaki and Marianne A. Azer
Information 2024, 15(1), 46; https://doi.org/10.3390/info15010046 - 14 Jan 2024
Cited by 1 | Viewed by 2231
Abstract
Ransomware is a type of malicious software that encrypts a victim’s files and demands payment in exchange for the decryption key. It is a rapidly growing and evolving threat that has caused significant damage and disruption to individuals and organizations around the world. [...] Read more.
Ransomware is a type of malicious software that encrypts a victim’s files and demands payment in exchange for the decryption key. It is a rapidly growing and evolving threat that has caused significant damage and disruption to individuals and organizations around the world. In this paper, we propose a comprehensive ransomware classification approach based on the comparison of similarity matrices derived from static, dynamic analysis, and visualization. Our approach involves the use of multiple analysis techniques to extract features from ransomware samples and to generate similarity matrices based on these features. These matrices are then compared using a variety of comparison algorithms to identify similarities and differences between the samples. The resulting similarity scores are then used to classify the samples into different categories, such as families, variants, and versions. We evaluate our approach using a dataset of ransomware samples and demonstrate that it can accurately classify the samples with a high degree of accuracy. One advantage of our approach is the use of visualization, which allows us to classify and cluster large datasets of ransomware in a more intuitive and effective way. In addition, static analysis has the advantage of being fast and accurate, while dynamic analysis allows us to classify and cluster packed ransomware samples. We also compare our approach to other classification approaches based on single analysis techniques and show that our approach outperforms these approaches in terms of classification accuracy. Overall, our study demonstrates the potential of using a comprehensive approach based on the comparison of multiple analysis techniques, including static analysis, dynamic analysis, and visualization, for the accurate and efficient classification of ransomware. It also highlights the importance of considering multiple analysis techniques in the development of effective ransomware classification methods, especially when dealing with large datasets and packed samples. Full article
(This article belongs to the Special Issue Wireless IoT Network Protocols II)
Show Figures

Figure 1

23 pages, 1629 KiB  
Article
In-Vehicle Network Intrusion Detection System Using Convolutional Neural Network and Multi-Scale Histograms
by Gianmarco Baldini
Information 2023, 14(11), 605; https://doi.org/10.3390/info14110605 - 8 Nov 2023
Cited by 1 | Viewed by 1931
Abstract
Cybersecurity in modern vehicles has received increased attention from the research community in recent years. Intrusion Detection Systems (IDSs) are one of the techniques used to detect and mitigate cybersecurity risks. This paper proposes a novel implementation of an IDS for in-vehicle security [...] Read more.
Cybersecurity in modern vehicles has received increased attention from the research community in recent years. Intrusion Detection Systems (IDSs) are one of the techniques used to detect and mitigate cybersecurity risks. This paper proposes a novel implementation of an IDS for in-vehicle security networks based on the concept of multi-scale histograms, which capture the frequencies of message identifiers in CAN-bus in-vehicle networks. In comparison to existing approaches in the literature based on a single histogram, the proposed approach widens the informative context used by the IDS for traffic analysis by taking into consideration sequences of two and three CAN-bus messages to create multi-scale dictionaries. The histograms are created from windows of in-vehicle network traffic. A preliminary multi-scale histogram model is created using only legitimate traffic. Against this model, the IDS performs traffic analysis to create a feature space based on the correlation of the histograms. Then, the created feature space is given in input to a Convolutional Neural Network (CNN) for the identification of the windows of traffic where the attack is present. The proposed approach has been evaluated on two different public data sets achieving a very competitive performance in comparison to the literature. Full article
(This article belongs to the Special Issue Wireless IoT Network Protocols II)
Show Figures

Figure 1

24 pages, 1930 KiB  
Article
Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things
by Abdelali Hadir, Naima Kaabouch, Mohammed-Alamine El Houssaini and Jamal El Kafi
Information 2023, 14(11), 592; https://doi.org/10.3390/info14110592 - 1 Nov 2023
Cited by 1 | Viewed by 1698
Abstract
Recently, the precise location of sensor nodes has emerged as a significant challenge in the realm of Internet of Things (IoT) applications, including Wireless Sensor Networks (WSNs). The accurate determination of geographical coordinates for detected events holds pivotal importance in these applications. Despite [...] Read more.
Recently, the precise location of sensor nodes has emerged as a significant challenge in the realm of Internet of Things (IoT) applications, including Wireless Sensor Networks (WSNs). The accurate determination of geographical coordinates for detected events holds pivotal importance in these applications. Despite DV-Hop gaining popularity due to its cost-effectiveness, feasibility, and lack of additional hardware requirements, it remains hindered by a relatively notable localization error. To overcome this limitation, our study introduces three new localization approaches that combine DV-Hop with Chicken Swarm Optimization (CSO). The primary objective is to improve the precision of DV-Hop-based approaches. In this paper, we compare the efficiency of the proposed localization algorithms with other existing approaches, including several algorithms based on Particle Swarm Optimization (PSO), while considering random network topologies. The simulation results validate the efficiency of our proposed algorithms. The proposed HW-DV-HopCSO algorithm achieves a considerable improvement in positioning accuracy compared to those of existing models. Full article
(This article belongs to the Special Issue Wireless IoT Network Protocols II)
Show Figures

Figure 1

24 pages, 2318 KiB  
Article
Evaluation of 60 GHz Wireless Connectivity for an Automated Warehouse Suitable for Industry 4.0
by Rahul Gulia, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf and Michael E. Kuhl
Information 2023, 14(9), 506; https://doi.org/10.3390/info14090506 - 15 Sep 2023
Viewed by 1107
Abstract
The fourth industrial revolution focuses on the digitization and automation of supply chains resulting in a significant transformation of methods for goods production and delivery systems. To enable this, automated warehousing is demanding unprecedented vehicle-to-vehicle and vehicle-to-infrastructure communication rates and reliability. The 60 [...] Read more.
The fourth industrial revolution focuses on the digitization and automation of supply chains resulting in a significant transformation of methods for goods production and delivery systems. To enable this, automated warehousing is demanding unprecedented vehicle-to-vehicle and vehicle-to-infrastructure communication rates and reliability. The 60 GHz frequency band can deliver multi-gigabit/second data rates to satisfy the increasing demands of network connectivity by smart warehouses. In this paper, we aim to investigate the network connectivity in the 60 GHz millimeter-wave band inside an automated warehouse. A key hindrance to robust and high-speed network connectivity, especially, at mmWave frequencies stems from numerous non-line-of-sight (nLOS) paths in the transmission medium due to various interacting objects such as metal shelves and storage boxes. The continual change in the warehouse storage configuration significantly affects the multipath reflected components and shadow fading effects, thus adding complexity to establishing stable, yet fast, network coverage. In this study, network connectivity in an automated warehouse is analyzed at 60 GHz using Network Simulator-3 (NS-3) channel simulations. We examine a simple warehouse model with several metallic shelves and storage materials of standard proportions. Our investigation indicates that the indoor warehouse network performance relies on the line-of-sight and nLOS propagation paths, the existence of reflective materials, and the autonomous material handling agents present around the access point (AP). In addition, we discuss the network performance under varied conditions including the AP height and storage materials on the warehouse shelves. We also analyze the network performance in each aisle of the warehouse in addition to its SINR heatmap to understand the 60 GHz network connectivity. Full article
(This article belongs to the Special Issue Wireless IoT Network Protocols II)
Show Figures

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Evaluation of 60 GHz Wireless Connectivity for an Automated Warehouse Suitable for Industry 4.0
Authors: Rahul Gulia; Abhishek Vashist; Amlan Ganguly; Clark Hochgraf; Michael E. Kuhl
Affiliation: Rochester Institute of Technology
Abstract: The fourth industrial revolution focuses on the digitization and automation of supply chains resulting in a significant transformation of methods for goods production and delivery systems. To enable this, automated warehousing is demanding unprecedented vehicle-to-vehicle and vehicle-to-infrastructure communication rates and reliability. The 60 GHz frequency band can deliver multi-gigabit/second data rates to satisfy the increasing demands of network connectivity by smart warehouses. In this paper, we aim to investigate the network connectivity in the 60 GHz millimeter wave band inside an automated warehouse. A key hindrance to robust and high-speed network connectivity, especially, at mmWave frequencies stems from numerous non-line-of-sight (nLOS) paths in the transmission medium due to various interacting objects such as metal shelves and storage boxes. The continual change in the warehouse storage configuration significantly affects the multipath reflected components and shadow-fading effects, thus adding complexity to establishing stable, yet fast, network coverage. In this study, network connectivity in an automated warehouse is analyzed at 60 GHz using Network Simulator-3 channel simulations. We examine a simple warehouse model with several metallic shelves and storage materials of standard proportions. Our investigation indicates that the indoor warehouse network performance relies on the line-of-sight and nLOS propagation paths, the existence of reflective materials, and the autonomous material handling agents present around the access point (AP). In addition, we discuss the network performance under varied conditions including the AP height and storage materials on the warehouse shelves. We also analyze the network performance in each aisle of the warehouse in addition to its SINR heatmap to understand the 60 GHz network connectivity.

Title: Blockchain-Enabled Agriculture: Employing IoT and AI for Better Data Management, Traceability, and Trustworthy
Authors: Ali Mansour
Affiliation: Lab STICC, ENSTA Bretagne, Brest 29200, France
Abstract: The integration of Internet of Things (IoT), artificial intelligence (AI), and blockchain technology is revolutionizing the agricultural industry. This paper explores the application of these technologies in smart agriculture, focusing on data management, traceability, and trustworthiness. The IoT-enabled smart agriculture ecosystem is presented, incorporating various IoT devices such as wireless sensors, IoT-based tractors, harvesting robots, smartphones, and UAVs for data collection and monitoring. Advanced agricultural practices, including genetic modification, greenhouse farming, vertical farming, and hydroponic systems, are discussed as solutions to enhance food production. Challenges in IoT implementation, including economic efficiency and technical issues, are addressed. The role of AI in smart agriculture is explored, highlighting its potential for increasing efficiency, productivity, and sustainability. Storage solutions, such as cloud platforms, edge computing, and blockchain, are presented for secure data management. The Challenges of implementing blockchain in agriculture are also discussed, including proof of ownership and investment. The project workflow is detailed, encompassing account registration, element and project creation, verification, rewards, and tasks. The paper concludes by emphasizing the transformative impact of these technologies on agriculture, while acknowledging the need for further research and development to ensure effective integration and realization of their benefits.

Back to TopTop