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Internet of Everything and Vehicular Networks
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Internet of Everything and Vehicular Networks

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Wireless Technologies".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 13406

Special Issue Editors

Prof. Dr. Vasco N. G. J. Soares

E-Mail Website
Guest Editor
1. Department of Computer Engineering, Polytechnic Institute of Castelo Branco, Av. Pedro Álvares Cabral, n° 12, 6000-084 Castelo Branco, Portugal
2. Instituto de Telecomunicações, Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal
3. AMA—Agência para a Modernização Administrativa, Rua de Santa Marta, n° 55, 1150-294 Lisboa, Portugal
Interests: vehicular networks; delay-/disruption-tolerant networks; Internet of Things; smart cities; smart farming
Special Issues, Collections and Topics in MDPI journals
Dr. João M. L. P. Caldeira

E-Mail Website
Guest Editor
1. Polytechnic Institute of Castelo Branco, Av. Pedro Álvares Cabral No 12, 6000-084 Castelo Branco, Portugal
2. Instituto de Telecomunicações, Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal
Interests: mobility support for wireless sensor networks; Internet of Things; smart cities; smart farming
Special Issues, Collections and Topics in MDPI journals
Dr. Jaime Galán-Jiménez

E-Mail Website
Guest Editor
Department of Computer and Telematic Systems Engineering, School of Technology, University of Extremadura, Avda. de la Universidad s/n, 10003 Cáceres, Spain
Interests: software-defined networking; unmanned aerial vehicles; 5G; edge–fog computing; network function virtualization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Everything is based on the idea of comprehensive connectivity, intelligence, and cognition between people, processes, data, and things, with the goal of converting information into actions for new intelligent capabilities and improved experiences. As one significant aspect of the Internet of Everything, vehicular networks provide network services in intelligent transportation systems, enabling a variety of applications for safety, traffic efficiency, driver assistance, and infotainment.

This Special Issue aims to assemble researchers, academicians, scientists, and students to exchange and share their experiences and research results on the most recent innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of the Internet of Everything and vehicular networks. The topics of this Special Issue include, but are not limited to, the following:

  • Technologies and standards;
  • Architectures, protocols, and algorithms;
  • Security, privacy, and trust;
  • Data management and analytics;
  • Theory, modelling, and simulation;
  • Network performance and management;
  • Prototypes, testbeds, and case studies;
  • Services and applications.

Prof. Dr. Vasco N. G. J. Soares
Dr. João M. L. P. Caldeira
Dr. Jaime Galán-Jiménez
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. 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 Everything
  • vehicular networks
  • architecture
  • protocol
  • algorithm
  • modelling
  • simulation
  • prototype
  • testbeds
  • services
  • applications

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

Published Papers (4 papers)

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Research

21 pages, 5950 KiB  
Article
A Contrastive Learning Framework for Vehicle Spatio-Temporal Trajectory Similarity in Intelligent Transportation Systems
by Qiang Tong, Zhi-Chao Xie, Wei Ni, Ning Li and Shoulu Hou
Information 2025, 16(3), 232; https://doi.org/10.3390/info16030232 - 16 Mar 2025
Viewed by 434
Abstract
The rapid development of vehicular networks has facilitated the extensive acquisition of vehicle trajectory data, which serve as a crucial cornerstone for a variety of intelligent transportation system (ITS) applications, such as traffic flow management and urban mobility optimization. Trajectory similarity computation has [...] Read more.
The rapid development of vehicular networks has facilitated the extensive acquisition of vehicle trajectory data, which serve as a crucial cornerstone for a variety of intelligent transportation system (ITS) applications, such as traffic flow management and urban mobility optimization. Trajectory similarity computation has become an essential tool for analyzing and understanding vehicle movements, making it indispensable for these applications. Nonetheless, most existing methods neglect the temporal dimension in trajectory analysis, limiting their effectiveness. To address this limitation, we integrate the temporal dimension into trajectory similarity evaluations and present a novel contrastive learning framework, termed Spatio-Temporal Trajectory Similarity with Contrastive Learning, aimed at training effective representations for spatio-temporal trajectory similarity. The STT-CL framework introduces the innovative concept of spatio-temporal grids and leverages two advanced grid embedding techniques to capture the coarse-grained features of spatio-temporal trajectory points. Moreover, we design a Spatio-Temporal Trajectory Cross-Fusion Encoder (STT-CFE) that seamlessly integrates coarse-grained and fine-grained features. Experiments on two large-scale real-world datasets demonstrate that STT-CL surpasses existing methods, underscoring its potential in trajectory-driven ITS applications. Full article
(This article belongs to the Special Issue Internet of Everything and Vehicular Networks)
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61 pages, 3860 KiB  
Article
A Comprehensive Survey of Threats in Platooning—A Cloud-Assisted Connected and Autonomous Vehicle Application
by Al Tariq Sheik, Carsten Maple, Gregory Epiphaniou and Mehrdad Dianati
Information 2024, 15(1), 14; https://doi.org/10.3390/info15010014 - 25 Dec 2023
Cited by 6 | Viewed by 3350
Abstract
Cloud-Assisted Connected and Autonomous Vehicles (CCAV) are set to revolutionise road safety, providing substantial societal and economic advantages. However, with the evolution of CCAV technology, security and privacy threats have increased. Although several studies have been published around the threat and risk estimation [...] Read more.
Cloud-Assisted Connected and Autonomous Vehicles (CCAV) are set to revolutionise road safety, providing substantial societal and economic advantages. However, with the evolution of CCAV technology, security and privacy threats have increased. Although several studies have been published around the threat and risk estimation aspects of CCAV, limited research exists on the security implications and emerging threat landscapes in the CCAV platooning application. We conducted an extensive review and categorisation of real-world security incidents and created an account of 132 threats from scholarly sources and 64 threats from recorded events in practice. Furthermore, we defined thirty-one (31) trust domains and outlined eight (8) unique attack vectors to supplement existing research efforts for the systematic security analysis of such cyberinfrastructures. Using these findings, we create a detailed attack taxonomy to communicate threat-related information in CCAV and platooning applications and highlight emerging challenges and ways to safeguard the broader CCAV systems. This work acts as a roadmap to existing researchers and practitioners advocating for a ‘security and privacy by design’ framework for a dynamically evolving CCAV threat landscape. Full article
(This article belongs to the Special Issue Internet of Everything and Vehicular Networks)
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24 pages, 4432 KiB  
Article
Vehicular Networks Dynamic Grouping and Re-Orchestration Scenarios
by Duaa Zuhair Al-Hamid and Adnan Al-Anbuky
Information 2023, 14(1), 32; https://doi.org/10.3390/info14010032 - 5 Jan 2023
Cited by 8 | Viewed by 2394
Abstract
The topological structure in vehicular communication networks presents challenges for sustaining network connectivity on the road. Highway dynamics, for example, encourage the need for an adaptive and flexible structure to handle the rapid events of vehicles joining and leaving the road. Such demand [...] Read more.
The topological structure in vehicular communication networks presents challenges for sustaining network connectivity on the road. Highway dynamics, for example, encourage the need for an adaptive and flexible structure to handle the rapid events of vehicles joining and leaving the road. Such demand aligns with the advancement made in software-defined networks and related dynamic network re-orchestration. This paper discusses the development of a virtual model that represents the operation of an autonomous vehicular network. It also investigates the ability to re-orchestrate the topology through software definition while running the various operational phases. Network self-formation, network expansion, retraction via vehicular members joining and leaving, and network self-healing when a topological rupture occurs as a result of a key member leaving the network are the key grouping phases. The communication approach is analyzed based on the status of network members and their ability to assume the various network roles. The concept is tested using both a Contiki–Cooja network simulator and a MATLAB analytical modeling tool to reflect the operation and performance of the grouping approach under various road scenarios. The outcome of the analysis reflects the ability of the group to be formulated within a measured latency considering the various network parameters such as communication message rate. The approach offers tools for managing the dynamic connectivity of vehicular groups and may also be extended to assume the function of an on-road network digital twin during the lifetime of a given group. Full article
(This article belongs to the Special Issue Internet of Everything and Vehicular Networks)
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15 pages, 4627 KiB  
Article
Performance Assessment of ESP8266 Wireless Mesh Networks
by Luís Santos, Tiago Costa, João M. L. P. Caldeira and Vasco N. G. J. Soares
Information 2022, 13(5), 210; https://doi.org/10.3390/info13050210 - 20 Apr 2022
Cited by 5 | Viewed by 5203
Abstract
This paper presents a wireless mesh network testbed based on ESP8266 devices using painlessMesh library. It evaluates its feasibility and potential effectiveness as a solution to monitor perishable goods, such as fresh fruit and vegetables, which are often stored and transported inside refrigerated [...] Read more.
This paper presents a wireless mesh network testbed based on ESP8266 devices using painlessMesh library. It evaluates its feasibility and potential effectiveness as a solution to monitor perishable goods, such as fresh fruit and vegetables, which are often stored and transported inside refrigerated containers. Performance testing experiments with different numbers of nodes and traffic loads and different message payload sizes are conducted under unicast transmission. The impact on network performance is evaluated in terms of delivery ratio and delivery delay, which, consequently, affect the energy consumption and, hence, network lifetime. The results of this investigation are an important contribution to help researchers to propose mechanisms, schemes, and protocols to improve performance in such challenging networks. Full article
(This article belongs to the Special Issue Internet of Everything and Vehicular Networks)
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