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Reliability Analysis of Wireless Sensor Network

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

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 14869

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Special Issue Editors

Prof. Dr. Lorenzo Ciani

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Guest Editor

DINFO-Department of Information Engineering, University of Florence, Via S.Marta, 3, 50139 Florence, Italy
Interests: reliability; availability; maintainability and safety (RAMS); testing

Dr. Gabriele Patrizi

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Guest Editor

Department of Information Engineering Florence, Univeristy of Florence, 50139 Florence, Italy
Interests: reliability; condition monitoring; remaining life assessment; maintenance engineering; temperature sensors; Monte Carlo methods; microsensors; soil; temperature measurement; DC-DC power convertors; artificial intelligence; failure analysis; geophysical techniques; life cycle costing; power engineering computing; secondary cells; units (measurement); wireless sensor networks; Global Positioning System; Internet of Things; Kalman filters; accelerometers; archaeology; battery management systems; fault diagnosis
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Special Issue Information

Dear Colleagues,

This Special Issue presents an interesting opportunity for engineers and researchers who work in this area to meet and discuss about the state-of-the-art, difficulties, innovations, and improvements in wireless sensor networks (WSNs) involved in components and system testing, fault diagnosis, condition monitoring, risk and safety assessment, and management that enable more reliable systems. These topics lead to advances in technology, instrumentation, and procedures that could push forward laboratory and university capabilities to develop more dependable wireless sensor networks and their validation, improve cooperation with accreditation, inspection and certification providers, and increase accuracy and compliance analysis, with a strong impact on the quality, reliability, and safety delivered to the environment, citizens, and customers on the global market.

Prospective authors can provide original contributions in this Special Issue which will cover the following aspects (but not limited to these):

Wireless sensor networks for testing and diagnostics;
Wireless sensor networks for condition monitoring and maintenance of industrial process, plants, and complex systems;
Wireless sensor networks for fault detection and diagnosis;
Reliable design and testing for wireless sensor networks;
Reliability, availability, maintainability, and safety (RAMS); risk assessment and management for wireless sensor networks.

Dr. Lorenzo Ciani
Dr. Gabriele Patrizi
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.

Published Papers (6 papers)

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Research

30 pages, 6523 KiB

Open AccessArticle

On the Challenges of Acoustic Energy Mapping Using a WASN: Synchronization and Audio Capture

by Emiliano Ehecatl García-Unzueta, Paul Erick Mendez-Monroy and Caleb Rascon

Sensors 2023, 23(10), 4645; https://doi.org/10.3390/s23104645 - 10 May 2023

Viewed by 1480

Abstract

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose. However, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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23 pages, 1408 KiB

Open AccessArticle

An Explainable Evolving Fuzzy Neural Network to Predict the k Barriers for Intrusion Detection Using a Wireless Sensor Network

by Paulo Vitor de Campos Souza, Edwin Lughofer and Huoston Rodrigues Batista

Sensors 2022, 22(14), 5446; https://doi.org/10.3390/s22145446 - 21 Jul 2022

Cited by 7 | Viewed by 1897

Abstract

Evolving fuzzy neural networks have the adaptive capacity to solve complex problems by interpreting them. This is due to the fact that this type of approach provides valuable insights that facilitate understanding the behavior of the problem being analyzed, because they can extract knowledge from a set of investigated data. Thus, this work proposes applying an evolving fuzzy neural network capable of solving data stream regression problems with considerable interpretability. The dataset is based on a necessary prediction of k barriers with wireless sensors to identify unauthorized persons entering a protected territory. Our method was empirically compared with state-of-the-art evolving methods, showing significantly lower RMSE values for separate test data sets and also lower accumulated mean absolute errors (MAEs) when evaluating the methods in a stream-based interleaved-predict-and-then-update procedure. In addition, the model could offer relevant information in terms of interpretable fuzzy rules, allowing an explainable evaluation of the regression problems contained in the data streams. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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23 pages, 3506 KiB

Open AccessArticle

Comprehensive Performance Analysis of Zigbee Communication: An Experimental Approach with XBee S2C Module

by Khandaker Foysal Haque, Ahmed Abdelgawad and Kumar Yelamarthi

Sensors 2022, 22(9), 3245; https://doi.org/10.3390/s22093245 - 23 Apr 2022

Cited by 9 | Viewed by 4386

Abstract

The recent development of wireless communications has prompted many diversified applications in both industrial and medical sectors. Zigbee is a short-range wireless communication standard that is based on IEEE 802.15.4 and is vastly used in both indoor and outdoor applications. Its performance depends on networking parameters, such as baud rates, transmission power, data encryption, hopping, deployment environment, and transmission distances. For optimized network deployment, an extensive performance analysis is necessary. This would facilitate a clear understanding of the trade-offs of the network performance metrics, such as the packet delivery ratio (PDR), power consumption, network life, link quality, latency, and throughput. This work presents an extensive performance analysis of both the encrypted and unencrypted Zigbee with the stated metrics in a real-world testbed, deployed in both indoor and outdoor scenarios. The major contributions of this work include (i) evaluating the most optimized transmission power level of Zigbee, considering packet delivery ratio and network lifetime; (ii) formulating an algorithm to find the network lifetime from the measured current consumption of packet transmission; and (iii) identifying and quantizing the trade-offs of the multi-hop communication and data encryption with latency, transmission range, and throughput. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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16 pages, 18721 KiB

Open AccessArticle

Reliability Analysis of Wireless Sensor Network for Smart Farming Applications

by Marcantonio Catelani, Lorenzo Ciani, Alessandro Bartolini, Cristiano Del Rio, Giulia Guidi and Gabriele Patrizi

Sensors 2021, 21(22), 7683; https://doi.org/10.3390/s21227683 - 18 Nov 2021

Cited by 16 | Viewed by 2851

Abstract

Wireless Sensor Networks are subjected to some design constraints (e.g., processing capability, storage memory, energy consumption, fixed deployment, etc.) and to outdoor harsh conditions that deeply affect the network reliability. The aim of this work is to provide a deeper understanding about the way redundancy and node deployment affect the network reliability. In more detail, the paper analyzes the design and implementation of a wireless sensor network for low-power and low-cost applications and calculates its reliability considering the real environmental conditions and the real arrangement of the nodes deployed in the field. The reliability of the system has been evaluated by looking for both hardware failures and communication errors. A reliability prediction based on different handbooks has been carried out to estimate the failure rate of the nodes self-designed and self-developed to be used under harsh environments. Then, using the Fault Tree Analysis the real deployment of the nodes is taken into account considering the Wi-Fi coverage area and the possible communication link between nearby nodes. The findings show how different node arrangements provide significantly different reliability. The positioning is therefore essential in order to obtain maximum performance from a Wireless sensor network. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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21 pages, 413 KiB

Open AccessArticle

A Framework for Analyzing Neighbor Discovery Protocols under Non-Ideal Conditions

by Jose Jaime Camacho-Escoto, Eduardo Lopez-Bolaños, Oscar Arana and Javier Gomez

Sensors 2021, 21(20), 6822; https://doi.org/10.3390/s21206822 - 14 Oct 2021

Viewed by 1213

Abstract

Neighbor Discovery (ND) protocols are crucial to achieving the paradigm of interconnecting thousands of small nodes (sensors or things) to the Internet, also known as the IoT. These protocols usually assume that nodes operate with few energy resources. Therefore, they cannot be fully active all the time. The vast majority of these protocols focus on increasing the probability that two nodes become active simultaneously, thus enabling mutual discovery. In addition, these protocols assume that successful discovery is guaranteed once two nodes are simultaneously active, with very few exceptions. However, many problems can disrupt the discovery, such as channel errors, collisions, synchronization mismatches, energy availability, and so forth. Most ND protocols did not consider these factors, making them vulnerable to severe performance degradation when transmission errors occur. This paper proposes a new framework to evaluate the performance of deterministic neighbor discovery protocols when transmission errors are present. The proposed framework facilitates obtaining an analytical CDF of the discovery time of such protocols with transmissions errors without having to implement the protocol in a simulator, since is time-consuming and prone to implementation errors. We applied the framework to analyze the effect of transmission errors on the discovery time in four of the most representative ND protocols in the literature. Finally, we validate the framework accuracy for the selected protocols using extensive simulations. The results show that the CDF of discovery times provided by the framework closely matches the performance results obtained through simulating these protocols. In general, neighbor discovery protocols are deeply affected as a result of transmission errors. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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16 pages, 4187 KiB

Open AccessArticle

PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

by Vahid Khalilpour Akram, Zuleyha Akusta Dagdeviren, Orhan Dagdeviren and Moharram Challenger

Sensors 2021, 21(19), 6418; https://doi.org/10.3390/s21196418 - 26 Sep 2021

Cited by 16 | Viewed by 1929

Abstract

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors. Full article

(This article belongs to the Special Issue Reliability Analysis of Wireless Sensor Network)

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