SFDWA: Secure and Fault-Tolerant Aware Delay Optimal Workload Assignment Schemes in Edge Computing for Internet of Drone Things Applications

Lakhan, Abdullah; Elhoseny, Mohamed; Mohammed, Mazin Abed; Jaber, Mustafa Musa

doi:10.1155/2022/5667012

Cited by 11 publications

(3 citation statements)

References 26 publications

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“…The research goal was to reduce response time, which was a combination of network, computation security and fault tolerant delay. Adopting various communication technologies was a significant challenge for IoDv, and it occasionally encountered issues due to limited energy resources [12]. Based on the application of various soft computing techniques, an adaptive-network-based fuzzy inference system (ANFIS) model was used to determine the induction motor fault.…”

Section: Background Of Related Workmentioning

confidence: 99%

SVM Algorithm for Vibration Fault Diagnosis in Centrifugal Pump

Dutta¹,

Palanisamy²,

Shanmugam³

2023

Intelligent Automation &Amp; Soft Computing

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Vibration failure in the pumping system is a significant issue for industries that rely on the pump as a critical device which requires regular maintenance. To save energy and money, a new automated system must be developed that can detect anomalies at an early stage. This paper presents a case study of a machine learning (ML)-based computational technique for automatic fault detection in a cascade pumping system based on variable frequency drive (VFD). Since the intensity of the vibrational effect depends on which axis has the most significant effect, a three-axis accelerometer is used to measure it in the pumping system. The emphasis is on determining the vibration effect on different axes. For experiment, various ML algorithms are investigated on collected vibratory data through Matlab software in x, y, z axes and performances of the algorithms are compared based on accuracy rate, prediction speed and training time. Based on the proposed research results, the multiclass support vector machine (MSVM) is found to be the best suitable algorithm compared to other algorithms. It has been demonstrated that ML algorithms can detect faults automatically rather than conventional methods. MSVM is used for the proposed work because it is less complex and produces better results with a limited data set.

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Section: Background Of Related Workmentioning

confidence: 99%

SVM Algorithm for Vibration Fault Diagnosis in Centrifugal Pump

Dutta¹,

Palanisamy²,

Shanmugam³

2023

Intelligent Automation &Amp; Soft Computing

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“…In addition, methods based on mathematical modeling are also applied to fault-related problems. Reference [9] studied fault tolerance and load distribution methods based on linear integer programming to meet the working requirements of edge computing.…”

Section: Fault Diagnosismentioning

confidence: 99%

Two-Stage Edge-Side Fault Diagnosis Method Based on Double Knowledge Distillation

Yang,

Long,

Lin

et al. 2023

Computers, Materials &Amp; Continua

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With the rapid development of the Internet of Things (IoT), the automation of edge-side equipment has emerged as a significant trend. The existing fault diagnosis methods have the characteristics of heavy computing and storage load, and most of them have computational redundancy, which is not suitable for deployment on edge devices with limited resources and capabilities. This paper proposes a novel two-stage edge-side fault diagnosis method based on double knowledge distillation. First, we offer a clustering-based self-knowledge distillation approach (Cluster KD), which takes the mean value of the sample diagnosis results, clusters them, and takes the clustering results as the terms of the loss function. It utilizes the correlations between faults of the same type to improve the accuracy of the teacher model, especially for fault categories with high similarity. Then, the double knowledge distillation framework uses ordinary knowledge distillation to build a lightweight model for edge-side deployment. We propose a two-stage edge-side fault diagnosis method (TSM) that separates fault detection and fault diagnosis into different stages: in the first stage, a fault detection model based on a denoising auto-encoder (DAE) is adopted to achieve fast fault responses; in the second stage, a diverse convolution model with variance weighting (DCMVW) is used to diagnose faults in detail, extracting features from micro and macro perspectives. Through comparison experiments conducted on two fault datasets, it is proven that the proposed method has high accuracy, low delays, and small computation, which is suitable for intelligent edge-side fault diagnosis. In addition, experiments show that our approach has a smooth training process and good balance.

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“…So here comes the role of cloud computing to make IoT more efficient by providing efficient communication links, storage capacity, real-time analysis, and a strong network backbone. The clubbing of these two technologies is known by many names, e.g., Cloud-centric Internet of Things (CIoT), CloudIoT, Cloud of Things (CoT) (Lakhan et al, 2022), etc.…”

Section: Introductionmentioning

confidence: 99%

Security issues and challenges in cloud of things-based applications for industrial automation

et al. 2023

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Due to the COVID-19 outbreak, industries have gained a thrust on contactless processing for computing technologies and industrial automation. Cloud of Things (CoT) is one of the emerging computing technologies for such applications. CoT combines the most emerging cloud computing and the Internet of Things. The development in industrial automation made them highly interdependent because the cloud computing works like a backbone in IoT technology. This supports the data storage, analytics, processing, commercial application development, deployment, and security compliances. Now amalgamation of cloud technologies with IoT is making utilities more useful, smart, service-oriented, and secure application for sustainable development of industrial processes. As the pandemic has increased access to computing utilities remotely, cyber-attacks have been increased exponentially. This paper reviews the CoT’s contribution to industrial automation and the various security features provided by different tools and applications used for the circular economy. The in-depth analysis of security threats, availability of different features corresponding the security issues in traditional and non-traditional CoT platforms used in industrial automation have been analysed. The security issues and challenges faced by IIoT and AIoT in industrial automation have also been addressed.

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SFDWA: Secure and Fault-Tolerant Aware Delay Optimal Workload Assignment Schemes in Edge Computing for Internet of Drone Things Applications

Cited by 11 publications

References 26 publications

SVM Algorithm for Vibration Fault Diagnosis in Centrifugal Pump

SVM Algorithm for Vibration Fault Diagnosis in Centrifugal Pump

Two-Stage Edge-Side Fault Diagnosis Method Based on Double Knowledge Distillation

Security issues and challenges in cloud of things-based applications for industrial automation

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