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Gotowe bibliografie tematyczne / WSN; Fault Model; BFRA

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Gotowa bibliografia na temat „WSN; Fault Model; BFRA”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "WSN; Fault Model; BFRA"

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Vijay, Kumar. "SURVEY OF FAULT DETECTION ALGORITHM IN WSN." INTERNATIONAL JOURNAL OF RESEARCH- GRANTHAALAYAH 5, no. 5 (2017): 207–13. https://doi.org/10.5281/zenodo.583910.

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In recent years, applications of wireless sensor networks (WSNs) have been improved due to its vast potential to connect the physical world to the virtual world. Also, a progress in microelectronic fabrication technology reduces cost of developed portable wireless sensor nodes. Faults occurring to sensor nodes are familiar due to the sensor device itself and the harsh environment where the sensor nodes are deploy. WSNs is mainly affect by the crash of sensor nodes. Possibility of sensor node failure increases with increase number of sensors. Wireless sensor networks have been recognized, at an

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Krishna, M. Sai Rama, Ch Jnana Gayathri, and K. Laxmi Pallavi Rao. "Building Fault Tolerance Within Wsn- A Topology Model." International Journal of Advances in Applied Sciences 7, no. 2 (2018): 135. http://dx.doi.org/10.11591/ijaas.v7.i2.pp135-142.

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<p>Wireless Sensor network plays a crucial role which helps in visualizing, processing, and analyzing the information wirelessly. WSN is a network which consists of huge amount of sensor devices which are of low cost and low powered also known as sensor nodes. These type of networks are generally used in real time applications such as monitoring of environmental conditions, militaries, industries etc.,.but the problem that exists in WSN is may be due to different failures such as node failure, link failure, sink failure, interference, power dissipation and collision. If these faults are

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M., Sai Rama Krishna, Jnana Gayathri Ch., and Laxmi Pallavi Rao K. "Building Fault Tolerance Within Wsn-A Topology Model." International Journal of Advances in Applied Sciences (IJAAS) 7, no. 2 (2018): 135–42. https://doi.org/10.11591/ijaas.v7.i2.pp135-142.

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Wireless Sensor network plays a crucial role which helps in visualizing, processing, and analyzing the information wirelessly. WSN is a network which consists of huge amount of sensor devices which are of low cost and low powered also known as sensor nodes. These type of networks are generally used in real time applications such as monitoring of environmental conditions, militaries, industries etc., .but the problem that exists in WSN is may be due to different failures such as node failure, link failure, sink failure, interference, power dissipation and collision. If these faults are unable t

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Mardenov, Yerik, Aigul Adamova, Tamara Zhukabayeva, and Mohamed Othman. "Enhancing Fault Detection in Wireless Sensor Networks Through Support Vector Machines: A Comprehensive Study." Journal of Robotics and Control (JRC) 4, no. 6 (2023): 868–77. http://dx.doi.org/10.18196/jrc.v4i6.20216.

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The Wireless Sensor Network (WSN) consists of many sensors that are distributed in a specific area for the purpose of monitoring physical conditions. Factors such as hardware limitations, limited resources, unfavourable WSN deployment environment, and the presence of various attacks on nodes can lead to the presence of Faulty Nodes in a WSN. This raises the problem of detecting Faulty Nodes and avoiding Data loss. Detecting Faulty Nodes in real-world scenarios will improve the quality of a WSN. The research was aimed at developing an algorithm to determine the location of Faulty Nodes in a WSN

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Smara, Mounya, and Al-Sakib Khan Pathan. "An Enhanced Mechanism for Fault Tolerance in Agricultural Wireless Sensor Networks." Network 4, no. 2 (2024): 150–74. http://dx.doi.org/10.3390/network4020008.

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Fault tolerance is a critical aspect for any wireless sensor network (WSN), which can be defined in plain terms as the quality of being dependable or performing consistently well. In other words, it may be described as the effectiveness of fault tolerance in the event of crucial component failures in the network. As a WSN is composed of sensors with constrained energy resources, network disconnections and faults may occur because of a power failure or exhaustion of the battery. When such a network is used for precision agriculture, which needs periodic and timely readings from the agricultural

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Hu, Jiamin, Xiaofan Yang, and Luxing Yang. "A Novel Diagnosis Scheme against Collusive False Data Injection Attack." Sensors 23, no. 13 (2023): 5943. http://dx.doi.org/10.3390/s23135943.

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The collusive false data injection attack (CFDIA) is a false data injection attack (FIDA), in which false data are injected in a coordinated manner into some adjacent pairs of captured nodes of an attacked wireless sensor network (WSN). As a result, the defense of WSN against a CFDIA is much more difficult than defense against ordinary FDIA. This paper is devoted to identifying the compromised sensors of a well-behaved WSN under a CFDIA. By establishing a model for predicting the reading of a sensor and employing the principal component analysis (PCA) technique, we establish a criterion for ju

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Xiao, Yang. "Dynamic Fault Tolerant Topology Control for Wireless Sensor Network Based on Node Cascading Failure." International Journal of Online Engineering (iJOE) 14, no. 05 (2018): 118. http://dx.doi.org/10.3991/ijoe.v14i05.8644.

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To address the node cascading failure (CF) of the wireless sensor networks (WSNs), considering such factors as node load and maximum capacity in scale-free topology, this paper establishes the WSN dynamic fault tolerant topology model based on node cascading failure, analyses the relationships between node load, topology and dynamic fault tolerance, and demonstrates the proposed model through simulation test. It studies the effects of topology parameter and load in case of random node failure in the network node cascading failure, and utilizes the theoretical derivation method to derive the st

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Vasco Arone Mazibuco, Nguyen Phuong Nhung, and Nguyen Tuan Linh. "Fault detection in wireless sensor networks with deep neural networks." Journal of Military Science and Technology, CSCE7 (December 30, 2023): 27–36. http://dx.doi.org/10.54939/1859-1043.j.mst.csce7.2023.27-36.

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This paper addresses the challenge of fault detection in Wireless Sensor Networks (WSNs), commonly used in fields like environmental monitoring and healthcare. WSNs, prone to various faults due to their deployment in unpredictable environments, require effective solutions for fault detection. Traditional machine learning approaches show limitations such as unsuitability for streaming data and the detection of a single fault type. We propose the use of deep neural networks, particularly Recurrent Neural Networks (RNNs), for fault detection in WSNs, focusing on temperature and humidity data. The

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Qin, Bo, Luyang Zhang, Heng Yin, and Yan Qin. "Multiple Feature Vectors Based Fault Classification for WSN Integrated Bearing of Rolling Mill." Journal of Control Science and Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/3041591.

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For rolling mill machines, the operation status of bearing has a close relationship with process safety and production effectiveness. Therefore, reliable fault diagnosis and classification are indispensable. Traditional methods always characterize fault feature using a single fault vector, which may fail to reveal whole fault influences caused by complex process disturbances. Besides, it may also lead to poor fault classification accuracy. To solve the above-mentioned problems, a fault extraction method is put forward to extract multiple feature vectors and then a classification model is devel

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Shakya, Subarna. "Pollination Inspired Clustering Model for Wireless Sensor Network Optimization." September 2021 3, no. 3 (2021): 196–207. http://dx.doi.org/10.36548/jsws.2021.3.006.

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Remote and dangerous fields that are expensive, complex, and unreachable to reach human insights are examined with ease using the Wireless Sensor Network (WSN) applications. Due to the use of non-renewable sources of energy, challenges with respect to the network lifetime, fault tolerance and energy consumption are faced by the self-managed networks. An efficient fault tolerance technique has been provided in this paper as an effective management strategy. Using the network and communication nodes, revitalization and fault recognition techniques are used for handling diverse levels of faults i

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Rozprawy doktorskie na temat "WSN; Fault Model; BFRA"

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Sridharan, Mukundan. "Design of Mobile and Static Sensor Fabrics." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306891061.

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Części książek na temat "WSN; Fault Model; BFRA"

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Sreedevi, Dr Pogula, Dr T. Santhi Sri, Dr E. Poornima, and Dr Farooq Sunar Mahammad. "IMPROVE FAULT DETECTION AND SENSOR ROUTING PROBLEMS WITH NAIVE BAYES CLASSIFIER AND DATA AGGREGATION APPROACH." In Futuristic Trends in IOT Volume 3 Book 6. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bbio6p2ch4.

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Wireless sensor networks are regularly located in hostile environments to observe changes in environmental factors. Broadening the importance of machine learning to WSN creates wonders and provides credibility to the system. Clustering in wireless sensor networks is a better technique to enhance energy utilization. This chapter uses an ensemble method for clustering and classification to develop machine-learning algorithms for fault detection in wireless sensor networks. We will propose a new routing protocol, Fault tolerance Backup cluster head, and Data Aggregation with Naïve Bayes Classifie

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Huang Hongwei and Zhang Dongming. "Quantitative Geotechnical Risk Management for Tunneling Projects in China." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-61.

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To date, the tunneling in China is experiencing an age of fast development for decades. The potential risks behind the huge amount of construction and operation works in China was first formally realized and managed after 2002. The transition of risk assessment from a qualitative manner to a quantitative manner is on the way from the research gradually to the practice. This paper tries to share some experiences in the quantitative risk management for tunneling in China by introducing novel techniques and associated practical applications. The fuzzy fault tree analysis is used for hazard identi

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Huang Hongwei and Zhang Dongming. "Quantitative Geotechnical Risk Management for Tunneling Projects in China." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-60.

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To date, the tunneling in China is experiencing an age of fast development for decades. The potential risks behind the huge amount of construction and operation works in China was first formally realized and managed after 2002. The transition of risk assessment from a qualitative manner to a quantitative manner is on the way from the research gradually to the practice. This paper tries to share some experiences in the quantitative risk management for tunneling in China by introducing novel techniques and associated practical applications. The fuzzy fault tree analysis is used for hazard identi

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Virendra, Mohit, Qi Duan, and Shambhu Upadhyaya. "Detecting Cheating Aggregators and Report Dropping Attacks in Wireless Sensor Networks." In Wireless Technologies. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-101-6.ch305.

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This chapter focuses on an important, challenging and yet largely unaddressed problem in Wireless Sensor Networks (WSN) data communication: detecting cheating aggregators and malicious/selfish discarding of data reports en route to the Base Stations (BSs). If undetected, such attacks can significantly affect the performance of applications. The goal is to make the aggregation process tamper-resistant so that the aggregator cannot report arbitrary values, and to ensure that silent discarding of data reports by intermediate en-route nodes is detected in a bounded fashion. In our model, individua

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Streszczenia konferencji na temat "WSN; Fault Model; BFRA"

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Begum, Beneyaz A., and N. V. Satyanarayana. "Composite interference mapping model for Interference Fault-Free Transmission in WSN." In 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2015. http://dx.doi.org/10.1109/icacci.2015.7275930.

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Lin, Lin. "An Intelligent Fault Diagnosis Model of WSN Based on Artificial Immune System." In 2020 5th International Conference on Smart Grid and Electrical Automation (ICSGEA). IEEE, 2020. http://dx.doi.org/10.1109/icsgea51094.2020.00093.

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Ren, Weizheng, Lianming Xu, and Zhongliang Deng. "Fault Diagnosis Model of WSN Based on Rough Set and Neural Network Ensemble." In 2008 Second International Symposium on Intelligent Information Technology Application. IEEE, 2008. http://dx.doi.org/10.1109/iita.2008.459.

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