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Electronics
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Cooperative and Cognitive Wireless Networks with IoT Applications
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Cooperative and Cognitive Wireless Networks with IoT Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 May 2024 | Viewed by 2375

Special Issue Editor

Dr. Hosam El-Ocla

E-Mail Website
Guest Editor
Department of Computer Science, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
Interests: computer communications; wireless networks; cooperative and cognitive networks; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on wireless data and information transmission and signal transfer to facilitate communications among the Internet of Things (IoT) devices of various applications and deployments. Cooperative networks are considered where IoT devices are able to communicate their cognitive information. Efficient network slicing for smart IoT devices communications is a crucial factor for the high performance of cognitive and 6G networks. Cognitive platforms to construct reliable radio systems and network architecture are considered in this issue. Vehicular cooperative and cognitive networks and applications are vital in smart cities, particularly with self-driven cars. Techniques across a wide range of data communications, information transfer, routing, admission control, collision avoidance, signals fading, traffic control, data security, and cognitive sensing in ad hoc networks are desired. Applications include smart homes, smart cities, e-health, self-driven vehicles, e-learning, etc.

I look forward to receiving your contributions. 

Dr. Hosam El-Ocla
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. 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

  • data communications among IoT devices
  • network slicing in 6G networks
  • vehicular cooperative and cognitive networks and applications
  • routing and traffic control in wireless networks
  • data security in wireless networks
  • cognitive sensing in ad hoc networks
  • IoT applications
  • cooperative networks
  • radio power signals transfer and fading

Published Papers (2 papers)

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Research

15 pages, 1056 KiB  
Article
Joint Optimization on Trajectory, Data Relay, and Wireless Power Transfer in UAV-Based Environmental Monitoring System
by Jaewook Lee and Haneul Ko
Electronics 2024, 13(5), 828; https://doi.org/10.3390/electronics13050828 - 21 Feb 2024
Viewed by 465
Abstract
In environmental monitoring systems based on the Internet of Things (IoT), sensor nodes (SNs) typically send data to the server via a wireless gateway (GW) at regular intervals. However, when SNs are located far from the GW, substantial energy is expended in transmitting [...] Read more.
In environmental monitoring systems based on the Internet of Things (IoT), sensor nodes (SNs) typically send data to the server via a wireless gateway (GW) at regular intervals. However, when SNs are located far from the GW, substantial energy is expended in transmitting data. This paper introduces a novel unmanned aerial vehicle (UAV)-based environmental monitoring system. In the proposed system, the UAV conducts patrols in the designated area, and SNs periodically transmit the collected data to the GW or the UAV. This transmission decision is made while taking into account the respective distance between both the GW and the UAV. To ensure a high-quality environmental map, characterized by a consistent collection of a satisfactory amount of up-to-date data while preventing energy depletion in the SNs and the UAV, the UAV periodically decides on three types of UAV operations. These decisions involve deciding where to move, deciding whether to relay or aggregate the data from the SNs, and deciding whether to transfer energy to the SNs. For the optimal decisions, we introduce an algorithm, called DeepUAV, using deep reinforcement learning (DRL) to make decisions in UAV operations. In DeepUAV, the controller continually learns online and enhances the UAV’s decisions through trial and error. The evaluation results indicate that DeepUAV successfully gathers a substantial amount of the current data consistently while mitigating the risk of energy depletion in SNs and the UAV. Full article
(This article belongs to the Special Issue Cooperative and Cognitive Wireless Networks with IoT Applications)
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19 pages, 6241 KiB  
Article
EBR: Routing Protocol to Detect Blackhole Attacks in Mobile Ad Hoc Networks
by Deepika Kancharakuntla and Hosam El-Ocla
Electronics 2022, 11(21), 3480; https://doi.org/10.3390/electronics11213480 - 26 Oct 2022
Viewed by 1047
Abstract
The presence of malevolent nodes in mobile ad hoc networks (MANETs) would lead to genuine security concerns. These nodes may disturb the routing process or deform the pattern of the data packets passing through the network. The MANET is extremely liable to attacks, [...] Read more.
The presence of malevolent nodes in mobile ad hoc networks (MANETs) would lead to genuine security concerns. These nodes may disturb the routing process or deform the pattern of the data packets passing through the network. The MANET is extremely liable to attacks, owing to its characteristics of the network framework, such as the absence of infrastructure, moveable topology, and a centralized control unit. One of the most common attacks in MANETs is the blackhole attack. MANET nodes are susceptible to spectacular degradation of network performance in the presence of such attacks. In this regard, detecting or preventing deceitful nodes that will launch blackhole attacks is a challenge in MANETs. In this paper, we propose an Enhanced Blackhole Resistance (EBR) protocol to identify and resist nodes that are responsible for blackhole attacks. EBR can avoid congested traffic by passing the data packets through a safe route with the minimum RTT. The EBR protocol uses a combination of time to live (TTL) and round trip time (RTT), which is also called a TR mechanism, to detect the blackhole attacks. Our algorithm does not require any cryptographic or authentication mechanisms. Simulation results prove that EBR behaves better than other protocols in terms of throughput, end-to-end delay, packet delivery ratio, energy, and routing overhead. Full article
(This article belongs to the Special Issue Cooperative and Cognitive Wireless Networks with IoT Applications)
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