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Symmetry
Special Issues
Research and Applications of Symmetric Sensor Networks
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Research and Applications of Symmetric Sensor Networks

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 7710

Special Issue Editors

Dr. Qinghe Zheng

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Guest Editor
School of Information Science and Engineering, Shandong University, Qingdao 266237, China
Interests: signal processing; computer vision; deep learning; neural network; image classification
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Guan Gui

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Co-Guest Editor
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Interests: intelligent signal analysis, signal sensing and recognition, AI-based wireless techniques
Special Issues, Collections and Topics in MDPI journals
Dr. Ruidan Su

E-Mail Website
Co-Guest Editor
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: machine learning; deep bi-direction learning; computational health; medical imaging; computer-aided diagnosis
Dr. Rui Yu

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Co-Guest Editor
lnstitute for Sustainable Manufacturing, University of Kentucky, Lexington, KY 40506, USA
Interests: welding; model predictive control

Special Issue Information

Dear Colleagues,

Internet-of-Things (IoT) technology is now triggering a new round of industrial revolution worldwide and has become an important force to drive social development. Symmetry plays an indispensable role in it. Wireless sensor networks (WSNs) in the sensing layer are composed of a large number of stationary or mobile sensors in a self-organized and multi-hop manner for collaboratively sensing, collecting, processing, and transmitting information of objects, and finally sending this information to the owner of the network. Compared with the traditional ad hoc network, WSN has the characteristics of self-organization, dynamics, reliability, and data centers, so it can be applied to places people cannot reach, such as the desert. At present, the structure and node layout of sensor networks are research hotspots. Some elegant or interpretable properties such as symmetry deserve to be discussed or studied, such as parity–time symmetry, structural symmetry, distribution symmetry, etc.

So far, the construction of sensor networks has been deeply studied by researchers worldwide, and corresponding sensing technology has been widely used and developed in applications. The purpose of this Special Issue is to gather a collection of articles on the latest research and developments in this field of research.

Dr. Qinghe Zheng
Dr. Guan Gui
Dr. Ruidan Su
Dr. Rui Yu
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. Symmetry 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 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

  • sensors
  • fixed-frequency sensors
  • sensor phenomena and characterization
  • wearable sensors
  • vision sensors
  • microwave sensors
  • sensor network
  • wireless communications
  • artificial neural network
  • modulation classification
  • cognitive radios

Published Papers (3 papers)

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Research

19 pages, 4675 KiB  
Article
Intelligent Computing Collaboration for the Security of the Fog Internet of Things
by Hong Zhao, Guowei Sun, Weiheng Li, Peiliang Zuo, Zhaobin Li and Zhanzhen Wei
Symmetry 2023, 15(5), 974; https://doi.org/10.3390/sym15050974 - 24 Apr 2023
Viewed by 1472
Abstract
The application of fog Internet of Things (IoT) technology helps solve the problem of weak computing power faced by IoT terminals. Due to asymmetric differences in communication methods, sensing data offloading from IoT terminals to fog and cloud layers faces different security issues, [...] Read more.
The application of fog Internet of Things (IoT) technology helps solve the problem of weak computing power faced by IoT terminals. Due to asymmetric differences in communication methods, sensing data offloading from IoT terminals to fog and cloud layers faces different security issues, and both processes should be protected through certain data transmission protection measures. To take advantage of the relative asymmetry between cloud, fog, and sensing layers, this paper considers using physical layer security technology and encryption technology to ensure the security of the sensing data unloading process. An efficient resource allocation method based on deep reinforcement learning is proposed to solve the problem of channel and power allocation in fog IoT scenarios, as well as the selection of unloading destinations. This problem, which is NP-hard, belongs to the attribute of mixed integer nonlinear programming. Meanwhile, the supporting parameters of the method, including state space, action space, and rewards, are all adaptively designed based on scene characteristics and optimization goals. The simulation and analysis show that the proposed method possesses good convergence characteristics. Compared to several heuristic methods, the proposed method reduces latency by at least 18.7% on the premise that the transmission of sensing data is securely protected. Full article
(This article belongs to the Special Issue Research and Applications of Symmetric Sensor Networks)
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16 pages, 3046 KiB  
Article
Symmetrical Simulation Scheme for Anomaly Detection in Autonomous Vehicles Based on LSTM Model
by Abdulaziz A. Alsulami, Qasem Abu Al-Haija, Ali Alqahtani and Raed Alsini
Symmetry 2022, 14(7), 1450; https://doi.org/10.3390/sym14071450 - 15 Jul 2022
Cited by 23 | Viewed by 3792
Abstract
Technological advancement has transformed traditional vehicles into autonomous vehicles. Autonomous vehicles play an important role since they are considered an essential component of smart cities. The autonomous vehicle is an intelligent vehicle capable of maintaining safe driving by avoiding crashes caused by drivers. [...] Read more.
Technological advancement has transformed traditional vehicles into autonomous vehicles. Autonomous vehicles play an important role since they are considered an essential component of smart cities. The autonomous vehicle is an intelligent vehicle capable of maintaining safe driving by avoiding crashes caused by drivers. Unlike traditional vehicles, which are fully controlled and operated by humans, autonomous vehicles collect information about the outside environment using sensors to ensure safe navigation. Autonomous vehicles reduce environmental impact because they usually use electricity to operate instead of fossil fuel, thus decreasing the greenhouse gasses. However, autonomous vehicles could be threatened by cyberattacks, posing risks to human life. For example, researchers reported that Wi-Fi technology could be vulnerable to cyberattacks through Tesla and BMW autonomous vehicles. Therefore, further research is needed to detect cyberattacks targeting the control components of autonomous vehicles to mitigate their negative consequences. This research will contribute to the security of autonomous vehicles by detecting cyberattacks in the early stages. First, we inject False Data Injection (FDI) attacks into an autonomous vehicle simulation-based system developed by MathWorks. Inc. Second, we collect the dataset generated from the simulation model after integrating the cyberattack. Third, we implement an intelligent symmetrical anomaly detection method to identify false data cyber-attacks targeting the control system of autonomous vehicles through a compromised sensor. We utilize long short-term memory (LSTM) deep networks to detect False Data Injection (FDI) attacks in the early stage to ensure the stability of the operation of autonomous vehicles. Our method classifies the collected dataset into two classifications: normal and anomaly data. The experimental result shows that our proposed model’s accuracy is 99.95%. To this end, the proposed model outperforms other state-of-the-art models in the same study area. Full article
(This article belongs to the Special Issue Research and Applications of Symmetric Sensor Networks)
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16 pages, 3767 KiB  
Article
Research on Real-Time Communication Algorithm of Substation Based on Time-Sensitive Network
by Beilei Wang, Yang Liu, Chenyang Guo, Yan Song, Jidong Wang, Jinchao Xiao and Xiaoguang Chen
Symmetry 2022, 14(6), 1170; https://doi.org/10.3390/sym14061170 - 07 Jun 2022
Cited by 1 | Viewed by 1500
Abstract
A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. [...] Read more.
A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations. Full article
(This article belongs to the Special Issue Research and Applications of Symmetric Sensor Networks)
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