Green fault detection scheme for IoT‐enabled wireless sensor networks

Author:

Chanak Prasenjit1ORCID,Banerjee Indrajit2,Bose Sagar2

Affiliation:

1. Department of Computer Science and Engineering Indian Institute of Technology (Banaras Hindu University) Varanasi India

2. Department of Information Technology Indian Institute of Engineering Science and Technology Shibpur India

Abstract

SummaryWireless sensor network (WSN) is one of the major components for the Internet of Things (IoT)‐based smart systems that accumulate meaningful information and send them to the end‐user. In IoT‐enabled WSNs, large numbers of sensor nodes are deployed in an on‐site environment to collect and transmit different physical parameters from the monitoring environments to a central repository. However, low‐cost sensing devices in IoT‐enabled WSNs are prone to fail due to energy depletion, software failures, and hardware failures. The existing fault detection approaches consume notable additional energy to detect and overcome the failures. As a result, the whole network is subject to premature death. This article proposes a green fault detection scheme for IoT‐enabled WSNs to detect faulty nodes and solve the premature death problem of the network. Furthermore, a faulty node reuse mechanism is proposed that significantly prolongs the network lifetime. We analyze the properties of the proposed algorithm mathematically and validate its performance through extensive simulation and real‐life experiments. The simulation and experimental results show improved performance of the proposed scheme in terms of fault detection accuracy, false alarm rate, and network lifetime.

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Reference31 articles.

1. Joint application admission control and network slicing in virtual sensor networks;Delgado C;IEEE Internet of Things J,2018

2. A roadmap for scalable agent organizations in the Internet of Everything;Schatten M;The J of Syst and Soft,2014

3. Wireless powered sensor networks for Internet of Things: maximum throughput and optimal power allocation;Chu Z;IEEE Internet of Things J,2018

4. Spatio‐temporal correlations for damages identification and localization in water pipeline systems based on WSNs;Ayadi A;Comp Netw,2020

5. Energy efficiency and economic impact investigations for air‐conditioners using wireless sensing and actuator networks;Qawasmi ARA;Energy Rep,2018

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Adaptive threshold based outlier detection on IoT sensor data: A node-level perspective;Alexandria Engineering Journal;2024-11

2. A Survey of Outlier Detection Techniques in IoT: Review and Classification;Journal of Sensor and Actuator Networks;2022-01-04

3. A Monitoring System and Faults Prediction for Internet of Things System;2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA);2021-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3