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Architectures, Protocols and Algorithms of Sensor Networks—Second Edition
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Architectures, Protocols and Algorithms of Sensor Networks—Second Edition

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

Deadline for manuscript submissions: 20 December 2025 | Viewed by 9673

Special Issue Editors

Prof. Dr. Bartłomiej Płaczek

E-Mail Website
Guest Editor
Institute of Computer Science, University of Silesia, 41-200 Sosnowiec, Poland
Interests: sensor networks; machine learning; intelligent transportation systems; sensor fusion; smart sensors; cellular automata
Special Issues, Collections and Topics in MDPI journals
Dr. Marcin Bernaś

E-Mail Website
Guest Editor
Department of Computer Science and Automatics, University of Bielsko-Biala, 43-309 Bielsko-Biala, Poland
Interests: sensor network; IoT; intelligent transport systems; vehicle detection; machine learning; edge computing; data fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue “Architectures, Protocols and Algorithms of Sensor Networks” (https://www.mdpi.com/journal/sensors/special_issues/architectures_protocols_algorithms_wsn), we are pleased to announce the next in the series, entitled “Architectures, Protocols and Algorithms of Sensor Networks—Second Edition”.

Sensor network technology provides new sources of information and opens perspectives for innovative applications in industry, smart cities, smart homes, healthcare, environmental monitoring, military, and other domains. The emerging sensor network applications require the development of new dedicated architectures, protocols, and algorithms that ensure reliable network operation for a long time, as well as cost-effective deployment, scalability, and seamless maintenance. Wireless sensor networks require efficient methods for power management. In various applications, the availability of accurate localization algorithms is also a prerequisite for success. Moreover, new solutions are necessary to ensure the usefulness and security of the information collected from sensor nodes.

This Special Issue is addressed to all types of architectures, protocols, and algorithms designed for innovative applications of sensor networks. Topics of interest include, but are not limited to, the following areas:

  • New architectures of wired and wireless sensor networks;
  • Application-aware communication protocols for sensor networks;
  • Data management in sensor networks;
  • Signal-processing algorithms for sensor networks;
  • In-network data processing and analysis;
  • Smart sensing and embedded machine learning algorithms;
  • Power management in wireless sensor networks;
  • Data transmission reduction in sensor networks;
  • Localization and tracking algorithms for sensor networks;
  • Mobility management in sensor networks;
  • Synchronization algorithms for sensor networks;
  • Information security in sensor networks.

Prof. Dr. Bartłomiej Płaczek
Dr. Marcin Bernaś
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.

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

Related Special Issue

Published Papers (4 papers)

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Research

19 pages, 342 KiB  
Article
Overview of Embedded Rust Operating Systems and Frameworks
by Thibaut Vandervelden, Ruben De Smet, Diana Deac, Kris Steenhaut and An Braeken
Sensors 2024, 24(17), 5818; https://doi.org/10.3390/s24175818 - 7 Sep 2024
Cited by 1 | Viewed by 2769
Abstract
Embedded Operating Systems (OSs) are often developed in the C programming language. Developers justify this choice by the performance that can be achieved, the low memory footprint, and the ease of mapping hardware to software, as well as the strong adoption by industry [...] Read more.
Embedded Operating Systems (OSs) are often developed in the C programming language. Developers justify this choice by the performance that can be achieved, the low memory footprint, and the ease of mapping hardware to software, as well as the strong adoption by industry of this programming language. The downside is that C is prone to security vulnerabilities unknowingly introduced by the software developer. Examples of such vulnerabilities are use-after-free, and buffer overflows. Like C, Rust is a compiled programming language that guarantees memory safety at compile time by adhering to a set of rules. There already exist a few OSs and frameworks that are entirely written in Rust, targeting sensor nodes. In this work, we give an overview of these OSs and frameworks and compare them on the basis of the features they provide, such as application isolation, scheduling, inter-process communication, and networking. Furthermore, we compare the OSs on the basis of the performance they provide, such as cycles and memory usage. Full article
(This article belongs to the Special Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition)
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21 pages, 1416 KiB  
Article
A Novel Medium Access Policy Based on Reinforcement Learning in Energy-Harvesting Underwater Sensor Networks
by Çiğdem Eriş, Ömer Melih Gül and Pınar Sarısaray Bölük
Sensors 2024, 24(17), 5791; https://doi.org/10.3390/s24175791 - 6 Sep 2024
Cited by 3 | Viewed by 1331
Abstract
Underwater acoustic sensor networks (UASNs) are fundamental assets to enable discovery and utilization of sub-sea environments and have attracted both academia and industry to execute long-term underwater missions. Given the heightened significance of battery dependency in underwater wireless sensor networks, our objective is [...] Read more.
Underwater acoustic sensor networks (UASNs) are fundamental assets to enable discovery and utilization of sub-sea environments and have attracted both academia and industry to execute long-term underwater missions. Given the heightened significance of battery dependency in underwater wireless sensor networks, our objective is to maximize the amount of harvested energy underwater by adopting the TDMA time slot scheduling approach to prolong the operational lifetime of the sensors. In this study, we considered the spatial uncertainty of underwater ambient resources to improve the utilization of available energy and examine a stochastic model for piezoelectric energy harvesting. Considering a realistic channel and environment condition, a novel multi-agent reinforcement learning algorithm is proposed. Nodes observe and learn from their choice of transmission slots based on the available energy in the underwater medium and autonomously adapt their communication slots to their energy harvesting conditions instead of relying on the cluster head. In the numerical results, we present the impact of piezoelectric energy harvesting and harvesting awareness on three lifetime metrics. We observe that energy harvesting contributes to 4% improvement in first node dead (FND), 14% improvement in half node dead (HND), and 22% improvement in last node dead (LND). Additionally, the harvesting-aware TDMA-RL method further increases HND by 17% and LND by 38%. Our results show that the proposed method improves in-cluster communication time interval utilization and outperforms traditional time slot allocation methods in terms of throughput and energy harvesting efficiency. Full article
(This article belongs to the Special Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition)
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11 pages, 807 KiB  
Communication
Performance Analysis of CSMA/NP under Finite Population Environments
by Ariadna I. Rodriguez-Gomez, Mario E. Rivero-Angeles, Izlian Y. Orea-Flores, Gina Gallegos-García and Juan Carlos Chimal-Eguia
Sensors 2024, 24(11), 3290; https://doi.org/10.3390/s24113290 - 21 May 2024
Viewed by 1315
Abstract
In this study, we analyze the CSMA Non-Persistent protocol with a finite number of nodes, providing more accurate results for applications like wireless sensor networks. The finite model addresses scenarios where the node count is moderate, capturing realistic system dynamics. Our analysis reveals [...] Read more.
In this study, we analyze the CSMA Non-Persistent protocol with a finite number of nodes, providing more accurate results for applications like wireless sensor networks. The finite model addresses scenarios where the node count is moderate, capturing realistic system dynamics. Our analysis reveals a dependency on the node count, impacting system throughput. As the node count increases, throughput behavior aligns with Kleinrock’s infinite model. We derive a complex closed-form throughput expression for a finite quantity of nodes in the system, solved numerically, and offer an approximate expression for specific conditions. These insights advance understanding of low-contention network performance, especially in scenarios where the infinite model becomes inadequate. Full article
(This article belongs to the Special Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition)
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19 pages, 1236 KiB  
Article
A Programmable Crypto-Processor for National Institute of Standards and Technology Post-Quantum Cryptography Standardization Based on the RISC-V Architecture
by Jihye Lee, Whijin Kim and Ji-Hoon Kim
Sensors 2023, 23(23), 9408; https://doi.org/10.3390/s23239408 - 25 Nov 2023
Cited by 4 | Viewed by 3338
Abstract
The advancement of quantum computing threatens the security of conventional public-key cryptosystems. Post-quantum cryptography (PQC) was introduced to ensure data confidentiality in communication channels, and various algorithms are being developed. The National Institute of Standards and Technology (NIST) has initiated PQC standardization, and [...] Read more.
The advancement of quantum computing threatens the security of conventional public-key cryptosystems. Post-quantum cryptography (PQC) was introduced to ensure data confidentiality in communication channels, and various algorithms are being developed. The National Institute of Standards and Technology (NIST) has initiated PQC standardization, and the selected algorithms for standardization and round 4 candidates were announced in 2022. Due to the large memory footprint and highly repetitive operations, there have been numerous attempts to accelerate PQC on both hardware and software. This paper introduces the RISC-V instruction set extension for NIST PQC standard algorithms and round 4 candidates. The proposed programmable crypto-processor can support a wide range of PQC algorithms with the extended RISC-V instruction set and demonstrates significant reductions in code size, the number of executed instructions, and execution cycle counts of target operations in PQC algorithms of up to 79%, 92%, and 87%, respectively, compared to RV64IM with optimization level 3 (-O3) in the GNU toolchain. Full article
(This article belongs to the Special Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition)
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