Energy Efficient Unequal Fault Tolerance Clustering Approach

Ramisetty, Sowjanya; Anand, Divya; Kavita, .; Verma, Sahil; Jhanjhi, N. Z.; Masud, Mehedi; Baz, Mohammed

doi:10.32604/csse.2022.021924

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Overall, this proved effective in simulating controlled structures and enabling autonomous monitoring. The authors of [51,52] investigated the monitoring of the vital signs of patients by using blockchain-based smart contracts. This system was designed using hyper ledger fabric and provided various benefits to individuals, irrespective of their location.…”

Section: H-iot In Blockchainmentioning

confidence: 99%

Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues

Kumar

Verma³

et al. 2023

Electronics

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Advancements in Healthcare Internet of Things (H-IoT) systems have created new opportunities and solutions for healthcare services, including the remote treatment and monitoring of patients. In addition, the security and privacy of personal health data must be ensured during data transfer. Security breaches in H-IoT can have serious safety and legal implications. This comprehensive review provides insights about secured data accession by employing cryptographic platforms such as H-IoT in big data, H-IoT in blockchain, H-IoT in machine learning and deep learning, H-IoT in edge computing, and H-IoT in software-defined networks. With this information, this paper reveals solutions to mitigate threats caused by different kinds of attacks. The prevailing challenges in H-IoT systems, including security and scalability challenges, real-time operating challenges, resource constraints, latency, and power consumption challenges are also addressed. We also discuss in detail the current trends in H-IoT, such as remote patient monitoring and predictive analytics. Additionally, we have explored future prospects, such as leveraging health data for informed strategic planning. A critical analysis performed by highlighting the prevailing limitations in H-IoT systems is also presented. This paper will hopefully provide future researchers with in-depth insights into the selection of appropriate cryptographic measures to adopt an energy-efficient and resource-optimized healthcare system.

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Section: H-iot In Blockchainmentioning

confidence: 99%

Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues

Kumar

Verma³

et al. 2023

Electronics

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“…The training and classification of blockchain comprise three security categories, namely Smart T, Mod T, and Avoid T for smart homes, which can be achieved through a neural network. The neural network is trained using a dataset of examples, and each example is labeled as either Smart T, Mod T, or Avoid T. The neural network learns to recognize patterns in the data that are associated with each of the three categories and then uses this knowledge to classify new examples [30,31]. The process of training a neural network involves adjusting the weights of its connections between neurons in order to minimize the loss function.…”

Section: The Data Selection For Rankingmentioning

confidence: 99%

Blockchain and Machine Learning Inspired Secure Smart Home Communication Network

Menon

Anand

Kavita

et al. 2023

Sensors

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With the increasing growth rate of smart home devices and their interconnectivity via the Internet of Things (IoT), security threats to the communication network have become a concern. This paper proposes a learning engine for a smart home communication network that utilizes blockchain-based secure communication and a cloud-based data evaluation layer to segregate and rank data on the basis of three broad categories of Transactions (T), namely Smart T, Mod T, and Avoid T. The learning engine utilizes a neural network for the training and classification of the categories that helps the blockchain layer with improvisation in the decision-making process. The contributions of this paper include the application of a secure blockchain layer for user authentication and the generation of a ledger for the communication network; the utilization of the cloud-based data evaluation layer; the enhancement of an SI-based algorithm for training; and the utilization of a neural engine for the precise training and classification of categories. The proposed algorithm outperformed the Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system, the data fusion technique, and artificial intelligence Internet of Things technology in providing electronic information engineering and analyzing optimization schemes in terms of the computation complexity, false authentication rate, and qualitative parameters with a lower average computation complexity; in addition, it ensures a secure, efficient smart home communication network to enhance the lifestyle of human beings.

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“…Therefore, data privacy and protection are important considerations in IoT healthcare systems with respect to data transmission [20]. Few researchers have proposed secure platforms or resources for healthcare systems based on IoT data transmission [21,22]. Therefore, in this study, we analyze a healthcare system in terms of computational duration, accuracy and development issues with the aim of arriving at a superior solution.…”

Section: Introductionmentioning

confidence: 99%

Challenges and Limitation Analysis of an IoT-Dependent System for Deployment in Smart Healthcare Using Communication Standards Features

Upadhyay¹,

Kumar

Upadhyay

et al. 2023

Sensors

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The use of IoT technology is rapidly increasing in healthcare development and smart healthcare system for fitness programs, monitoring, data analysis, etc. To improve the efficiency of monitoring, various studies have been conducted in this field to achieve improved precision. The architecture proposed herein is based on IoT integrated with a cloud system in which power absorption and accuracy are major concerns. We discuss and analyze development in this domain to improve the performance of IoT systems related to health care. Standards of communication for IoT data transmission and reception can help to understand the exact power absorption in different devices to achieve improved performance for healthcare development. We also systematically analyze the use of IoT in healthcare systems using cloud features, as well as the performance and limitations of IoT in this field. Furthermore, we discuss the design of an IoT system for efficient monitoring of various healthcare issues in elderly people and limitations of an existing system in terms of resources, power absorption and security when implemented in different devices as per requirements. Blood pressure and heartbeat monitoring in pregnant women are examples of high-intensity applications of NB-IoT (narrowband IoT), technology that supports widespread communication with a very low data cost and minimum processing complexity and battery lifespan. This article also focuses on analysis of the performance of narrowband IoT in terms of delay and throughput using single- and multinode approaches. We performed analysis using the message queuing telemetry transport protocol (MQTTP), which was found to be efficient compared to the limited application protocol (LAP) in sending information from sensors.

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Energy Efficient Unequal Fault Tolerance Clustering Approach

Cited by 5 publications

References 30 publications

Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues

Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues

Blockchain and Machine Learning Inspired Secure Smart Home Communication Network

Challenges and Limitation Analysis of an IoT-Dependent System for Deployment in Smart Healthcare Using Communication Standards Features

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