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An Intelligent Fault Tolerant Data Routing Scheme for Wireless Sensor Network-Assisted Industrial Internet of Things | IEEE Journals & Magazine | IEEE Xplore

An Intelligent Fault Tolerant Data Routing Scheme for Wireless Sensor Network-Assisted Industrial Internet of Things


Abstract:

Safety is a major concern for Industrial 4.0 where different physical parameters are monitored for avoiding uncertain events in the industry. In industries, natural calam...Show More

Abstract:

Safety is a major concern for Industrial 4.0 where different physical parameters are monitored for avoiding uncertain events in the industry. In industries, natural calamities like fire and leakage of harmful gases can cause huge damage to life and property. An Industrial Internet of Things (IIoT) is used to monitor such natural calamities and take timely prompt actions. However, sensors in the IIoT are vulnerable to failures due to energy depletion and hardware malfunctioning. It significantly reduces the reliability of the network. This article proposes an intelligent fault-tolerant scheme where different faults within the wireless sensor network-assisted IIoT such as node fault and link fault are detected and tolerated in a timely manner. It significantly improves the reliability of the network. Extensive simulations show the out-performance of the proposed scheme in terms of average packet delivery, energy consumption, throughput, network lifetime, communication delay, and recovery speed.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 19, Issue: 4, April 2023)
Page(s): 5543 - 5553
Date of Publication: 06 September 2022

ISSN Information:

Funding Agency:

Author image of Gagandeep Kaur
School of Computer Science Engineering and Technology, Bennett University, Greater Noida, UP, India
Gagandeep Kaur (Graduate Student Member, IEEE) received the Ph.D. degree in computer science and engineering from the Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India, in 2022.
She is currently an Assistant Professor with Bennett University, Greater Noida, India. She has published various research articles in reputed international journals and conferences. Her resea...Show More
Gagandeep Kaur (Graduate Student Member, IEEE) received the Ph.D. degree in computer science and engineering from the Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India, in 2022.
She is currently an Assistant Professor with Bennett University, Greater Noida, India. She has published various research articles in reputed international journals and conferences. Her resea...View more
Author image of Prasenjit Chanak
Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, UP, India
Prasenjit Chanak (Member, IEEE) received the M.Tech and Ph.D. degrees in information technology from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India, in 2011 and 2016, respectively.
He is currently an Assistant Professor with Indian Institute of Technology (BHU), Varanasi, India. From December 2016 to August 2020, he also served as an Assistant Professor with the Department of Information...Show More
Prasenjit Chanak (Member, IEEE) received the M.Tech and Ph.D. degrees in information technology from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India, in 2011 and 2016, respectively.
He is currently an Assistant Professor with Indian Institute of Technology (BHU), Varanasi, India. From December 2016 to August 2020, he also served as an Assistant Professor with the Department of Information...View more

I. Introduction

Nowadays, Industrial 4.0 has become a hot topic of research as it has revolutionized the industrial sector. In Industrial 4.0, different cutting edge technologies such as Industrial Internet of Things (IIoT), industrial wireless sensor networks (IWSNs), and machine learning are used for the advancement and automation of traditional industrial processes [1]. Industry 4.0 introduces smart machines such as autonomous robots, expert systems, and intelligent assistants. Smart machines significantly increase the productivity and safety of an industry. As per the current report [2], the global smart machine market will reach $32.5 billion by 2027. In this industrial revolution, heterogeneous sensors are deployed to monitor different physical parameters of the industrial environment. Different sensor nodes form a wireless sensor network that can directly assist different IIoT applications. Intelligent wireless sensor networks (WSNs) find different applications in Industry 4.0 including healthcare [3], safety [4], and smart manufacturing [5]. Intelligence is introduced in IIoT with the use of artificial intelligence (AI). As per the Internet of Things (IoT) Tech news report [6], the annual growth rate of incorporation of AI in IIoT is expected to be 57.2% over the next five years.

Author image of Gagandeep Kaur
School of Computer Science Engineering and Technology, Bennett University, Greater Noida, UP, India
Gagandeep Kaur (Graduate Student Member, IEEE) received the Ph.D. degree in computer science and engineering from the Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India, in 2022.
She is currently an Assistant Professor with Bennett University, Greater Noida, India. She has published various research articles in reputed international journals and conferences. Her research interests include wireless sensor networks, Internet of Things, soft computing, and machine learning.
Gagandeep Kaur (Graduate Student Member, IEEE) received the Ph.D. degree in computer science and engineering from the Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India, in 2022.
She is currently an Assistant Professor with Bennett University, Greater Noida, India. She has published various research articles in reputed international journals and conferences. Her research interests include wireless sensor networks, Internet of Things, soft computing, and machine learning.View more
Author image of Prasenjit Chanak
Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, UP, India
Prasenjit Chanak (Member, IEEE) received the M.Tech and Ph.D. degrees in information technology from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India, in 2011 and 2016, respectively.
He is currently an Assistant Professor with Indian Institute of Technology (BHU), Varanasi, India. From December 2016 to August 2020, he also served as an Assistant Professor with the Department of Information and Communications Technology, Atal Bihari Vajpayee-Indian Institute of Information Technology and Management, Gwalior, India. He has executed various government of India-sponsored projects from DST, ICSSR, and SERB. He has authored or coauthored more than 60 research papers in different reputed international journals and conferences. He has published five Indian patents. His research interests are wireless sensor networks, Internet of Things (IoT), cyber-physical networks (CPN), machine learning, and consumer electronics systems.
Prasenjit Chanak (Member, IEEE) received the M.Tech and Ph.D. degrees in information technology from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India, in 2011 and 2016, respectively.
He is currently an Assistant Professor with Indian Institute of Technology (BHU), Varanasi, India. From December 2016 to August 2020, he also served as an Assistant Professor with the Department of Information and Communications Technology, Atal Bihari Vajpayee-Indian Institute of Information Technology and Management, Gwalior, India. He has executed various government of India-sponsored projects from DST, ICSSR, and SERB. He has authored or coauthored more than 60 research papers in different reputed international journals and conferences. He has published five Indian patents. His research interests are wireless sensor networks, Internet of Things (IoT), cyber-physical networks (CPN), machine learning, and consumer electronics systems.View more
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