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Advances in Wireless Ad-Hoc and Sensor Networks towards 6G
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Advances in Wireless Ad-Hoc and Sensor Networks towards 6G

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 25 May 2024 | Viewed by 1787

Special Issue Editors

Dr. Marica Amadeo

E-Mail Website
Guest Editor
DIIES Department, University Mediterranea of Reggio Calabria, 89100 Reggio Calabria, Italy
Interests: information-centric networking; vehicular ad hoc networks; mobile ad hoc networks; Internet of Things; edge computing; software-defined networking
Special Issues, Collections and Topics in MDPI journals
Dr. Chaker Abdelaziz Kerrache

E-Mail Website
Guest Editor
Laboratoire d’Informatique et de Mathématiques, Université Amar Telidji de Laghouat, Laghouat 03000, Algeria
Interests: security, privacy and trust; vehicular networks; named data networking (NDN); unmanned aerial vehicles; brain-to-computer interface (BCI); smart cities
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Ruggeri

E-Mail Website
Guest Editor
DIIES Department, University Mediterranea of Reggio Calabria, 89100 Reggio Calabria, Italy
Interests: interconnection-integration of heterogeneous wireless networks; self-organizing networks; Internet of Things (IoT); Social Internet of Things (SIoT) and M2M communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The upcoming immersive 6G applications demand ultra-low latency data collection from Wireless Ad Hoc and Sensor Networks and for the fast processing of those data, possibly at the Edge of the network.

Such requirements are hard to be met in the presence of billions of sensors and other (sometimes intermittently) connected devices in a variety of ambitious scenarios, ranging from Intelligent Transportation Systems (ITS), cognitive environments, and Extended Reality, to healthcare and Industrial Internet of Things (IIoT). Indeed, despite the high expectations, Wireless Ad Hoc and Sensor Networks are still challenged by energy, security, and communication issues.

The recent advances in Artificial Intelligence (AI) technologies and the advent of future networking paradigms can represent a promising solution to guarantee the requirements of 6G applications while maintaining ad hoc and sensor devices operational for a long time.

On the one side, AI solutions, like machine learning techniques, can help increase security, and improve routing functions and energy efficiency. On the other side, revolutionary networking paradigms, like Information-Centric Networking, can facilitate data dissemination and processing and service provisioning.

This Special Issue aims at collecting works targeting the recent advances in Wireless Ad Hoc and Sensor Networks to support future 6G applications and services. Original research and comprehensive reviews are welcome.

Dr. Marica Amadeo
Dr. Chaker Abdelaziz Kerrache
Dr. Giuseppe Ruggeri
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. Sensors 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

  • machine learning solutions for wireless ad hoc and sensor networks 
  • federated learning solutions for wireless ad hoc and sensor networks 
  • wireless ad hoc and sensor networks for future 6G applications 
  • information centric networking for wireless ad hoc and sensor networks 
  • smart routing solutions in sensor networks 
  • caching strategies in wireless ad hoc and sensor networks 
  • wireless ad hoc and sensor networks in cognitive environments 
  • UAV applications to wireless ad hoc and sensor networks 
  • edge computing in wireless ad hoc and sensor networks 
  • testbeds and real world applications

Published Papers (2 papers)

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21 pages, 565 KiB  
Article
Secure Computing for Fog-Enabled Industrial IoT
by Ahmad Naseem Alvi, Bakhtiar Ali, Mohamed Saad Saleh, Mohammed Alkhathami, Deafallah Alsadie and Bushra Alghamdi
Sensors 2024, 24(7), 2098; https://0-doi-org.brum.beds.ac.uk/10.3390/s24072098 - 25 Mar 2024
Viewed by 440
Abstract
Smart cities are powered by several new technologies to enhance connectivity between devices and develop a network of connected objects which can lead to many smart industrial applications. This network known as the Industrial Internet of Things (IIoT) consists of sensor nodes that [...] Read more.
Smart cities are powered by several new technologies to enhance connectivity between devices and develop a network of connected objects which can lead to many smart industrial applications. This network known as the Industrial Internet of Things (IIoT) consists of sensor nodes that have limited computing capacity and are sometimes not able to execute intricate industrial tasks within their stipulated time frame. For faster execution, these tasks are offloaded to nearby fog nodes. Internet access and the diverse nature of network types make IIoT nodes vulnerable and are under serious malicious attacks. Malicious attacks can cause anomalies in the IIoT network by overloading complex tasks, which can compromise the fog processing capabilities. This results in an increased delay of task computation for trustworthy nodes. To improve the task execution capability of the fog computing node, it is important to avoid complex offloaded tasks due to malicious attacks. However, even after avoiding the malicious tasks, if the offloaded tasks are too complex for the fog node to execute, then the fog nodes may struggle to process all legitimate tasks within their stipulated time frame. To address these challenges, the Trust-based Efficient Execution of Offloaded IIoT Trusted tasks (EEOIT) is proposed for fog nodes. EEOIT proposes a mechanism to detect malicious nodes as well as manage the allocation of computing resources so that IIoT tasks can be completed in the specified time frame. Simulation results demonstrate that EEOIT outperforms other techniques in the literature in an IIoT setting with different task densities. Another significant feature of the proposed EEOIT technique is that it enhances the computation of trustable tasks in the network. The results show that EEOIT entertains more legitimate nodes in executing their offloaded tasks with more executed data, with reduced time and with increased mean trust values as compared to other schemes. Full article
(This article belongs to the Special Issue Advances in Wireless Ad-Hoc and Sensor Networks towards 6G)
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24 pages, 1725 KiB  
Article
Multiple Precaching Vehicle Selection Scheme Based on Set Ranking in Intermittently Connected Vehicular Networks
by Youngju Nam, Jaejeong Bang, Hyunseok Choi, Yongje Shin, Seungmin Oh and Euisin Lee
Sensors 2023, 23(13), 5800; https://0-doi-org.brum.beds.ac.uk/10.3390/s23135800 - 21 Jun 2023
Viewed by 710
Abstract
In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, [...] Read more.
In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, vehicular networks can feature uncovered outage zones between two neighboring RSUs. In these outage zones, vehicles cannot download content, and thus the vehicle networks are defined as intermittently connected vehicular networks. In intermittently connected vehicular networks, the download delay and traffic overhead on the backhaul links are increased due to the large size of the content requested by vehicle users and the long distances between RSUs. Using the mobility information of vehicles, several schemes have been proposed to solve this issue by precaching and relaying content via multiple relaying vehicles in the outage zone. However, because they involved the individual ranking of vehicles for precaching and allocated all of the available precaching amounts to the top-ranking vehicles, they decreased the success rate of content requests and the fairness of vehicle precaching. To overcome the problem of these previous schemes, this paper proposes a multiple precaching vehicle selection (MPVS) scheme that efficiently selects a content-precaching vehicle group with multiple precaching vehicles to precache relayed content in outage zones. To achieve this, we first designed numerical models to decide the necessity and the amount of precaching and to calculate the available precaching amounts of vehicles. Next, MPVS calculates all available vehicle sets and ranks each set based on the available precaching amount. Then, the content-precaching vehicle group is identified from the sets by considering both set rankings and vehicle communication overheads. MPVS also provides a content downloading process through the content-precaching vehicle group in the outage zone. Simulation results conducted in various environments with a content request model and a highway mobility model verified that MPVS was superior to a representative previous scheme. Full article
(This article belongs to the Special Issue Advances in Wireless Ad-Hoc and Sensor Networks towards 6G)
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