Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions

The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision,...

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Main Authors: Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia
Format: Article
Published: Multidisciplinary Digital Publishing Institute 2022
Online Access:http://psasir.upm.edu.my/id/eprint/101502/
https://www.mdpi.com/1424-8220/22/16/6041
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.1015022023-06-15T21:31:25Z http://psasir.upm.edu.my/id/eprint/101502/ Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions Adday, Ghaihab Hassan K. Subramaniam, Shamala Ahmad Zukarnain, Zuriati Samian, Normalia The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision, in which the environment becomes intelligent and aware of its surroundings. WSN has unique features which create its own distinct network attributes and is deployed widely for critical real-time applications that require stringent prerequisites when dealing with faults to ensure the avoidance and tolerance management of catastrophic outcomes. Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. Fault tolerance structures contain three fundamental stages: error detection, error diagnosis, and error recovery. The emergence of analytics and the depth of harnessing it has led to the development of new fault-tolerant structures and strategies based on artificial intelligence and cloud-based. This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. Subsequently, an extensive analysis of existing fault tolerance techniques based on eight constraints is presented. Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. A new taxonomy of comparison that also extensively reviews previous surveys and state-of-the-art scientific articles based on different factors is discussed and provides the basis for the proposed open issues. Multidisciplinary Digital Publishing Institute 2022-08-12 Article PeerReviewed Adday, Ghaihab Hassan and K. Subramaniam, Shamala and Ahmad Zukarnain, Zuriati and Samian, Normalia (2022) Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions. Sensors, 22 (16). art. no. 6041. pp. 1-39. ISSN 1424-8239; ESSN: 1424-8220 https://www.mdpi.com/1424-8220/22/16/6041 10.3390/s22166041
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision, in which the environment becomes intelligent and aware of its surroundings. WSN has unique features which create its own distinct network attributes and is deployed widely for critical real-time applications that require stringent prerequisites when dealing with faults to ensure the avoidance and tolerance management of catastrophic outcomes. Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. Fault tolerance structures contain three fundamental stages: error detection, error diagnosis, and error recovery. The emergence of analytics and the depth of harnessing it has led to the development of new fault-tolerant structures and strategies based on artificial intelligence and cloud-based. This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. Subsequently, an extensive analysis of existing fault tolerance techniques based on eight constraints is presented. Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. A new taxonomy of comparison that also extensively reviews previous surveys and state-of-the-art scientific articles based on different factors is discussed and provides the basis for the proposed open issues.
format Article
author Adday, Ghaihab Hassan
K. Subramaniam, Shamala
Ahmad Zukarnain, Zuriati
Samian, Normalia
spellingShingle Adday, Ghaihab Hassan
K. Subramaniam, Shamala
Ahmad Zukarnain, Zuriati
Samian, Normalia
Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
author_facet Adday, Ghaihab Hassan
K. Subramaniam, Shamala
Ahmad Zukarnain, Zuriati
Samian, Normalia
author_sort Adday, Ghaihab Hassan
title Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
title_short Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
title_full Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
title_fullStr Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
title_full_unstemmed Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
title_sort fault tolerance structures in wireless sensor networks (wsns): survey, classification, and future directions
publisher Multidisciplinary Digital Publishing Institute
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/101502/
https://www.mdpi.com/1424-8220/22/16/6041
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