An SDN-Enabled IoT Architecture with Fog Computing and Edge Encryption Support

Asif, Md. Rashid Al; Mahfuz, Nagib; Momin, Md. Abdul

doi:10.1007/978-981-15-3607-6_33

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…In [119] authors proposed IoT gateway based on mobile phone for transmission of data over wide area network(WAN). IoT gateway with the capability of data requests and replies translations is proposed in [120]. The data is collected from IoT sensors and transmitted to applications installed on the mobile phone.…”

Section: Background Of Iotmentioning

confidence: 99%

A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

et al. 2021

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In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of data. One major contribution to the research world is in the form of software-defined networking applications, which aim to deploy rule-based management to control and add intelligence to the network using high-level policies to have integral control of the network without knowing issues related to low-level configurations. Machine learning techniques coupled with software-defined networking can make the networking decision more intelligent and robust. The Internet of Things application has recently adopted virtualization of resources and network control with software-defined networking policies to make the traffic more controlled and maintainable. However, the requirements of software-defined networking and the Internet of Things must be aligned to make the adaptations possible. This paper aims to discuss the possible ways to make software-defined networking enabled Internet of Things application and discusses the challenges solved using the Internet of Things leveraging the software-defined network. We provide a topical survey of the application and impact of software-defined networking on the Internet of things networks. We also study the impact of machine learning techniques applied to software-defined networking and its application perspective. The study is carried out from the different perspectives of software-based Internet of Things networks, including wide-area networks, edge networks, and access networks. Machine learning techniques are presented from the perspective of network resources management, security, classification of traffic, quality of experience, and quality of service prediction. Finally, we discuss challenges and issues in adopting machine learning and software-defined networking for the Internet of Things applications.

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Section: Background Of Iotmentioning

confidence: 99%

A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

et al. 2021

View full text Add to dashboard Cite

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“…Scientific community introduced efficient IoT architecture-based smart gateway to tackle the data trimming issue [64][65][66] . Data collection, pre-processing, data filtering, and data reconstruction into a more valued format are some of the operations performed by these smart gateways [67][68][69].…”

Section: Internet Of Thingsmentioning

confidence: 99%

Comprehensive Survey of IoT, Machine Learning, and Blockchain for Health Care Applications: A Topical Assessment for Pandemic Preparedness, Challenges, and Solutions

Imran

Zaman²,

Imran

et al. 2021

Electronics

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Internet of Things (IoT) communication technologies have brought immense revolutions in various domains, especially in health monitoring systems. Machine learning techniques coupled with advanced artificial intelligence techniques detect patterns associated with diseases and health conditions. Presently, the scientific community is focused on enhancing IoT-enabled applications by integrating blockchain technology with machine learning models to benefit medical report management, drug traceability, tracking infectious diseases, etc. To date, contemporary state-of-the-art techniques have presented various efforts on the adaptability of blockchain and machine learning in IoT applications; however, there exist various essential aspects that must also be incorporated to achieve more robust performance. This study presents a comprehensive survey of emerging IoT technologies, machine learning, and blockchain for healthcare applications. The reviewed articles comprise a plethora of research articles published in the web of science. The analysis is focused on research articles related to keywords such as `machine learning’, blockchain, `Internet of Things or IoT’, and keywords conjoined with `healthcare’ and `health application’ in six famous publisher databases, namely IEEEXplore, Nature, ScienceDirect, MDPI, SpringerLink, and Google Scholar. We selected and reviewed 263 articles in total. The topical survey of the contemporary IoT-based models is presented in healthcare domains in three steps. Firstly, a detailed analysis of healthcare applications of IoT, blockchain, and machine learning demonstrates the importance of the discussed fields. Secondly, the adaptation mechanism of machine learning and blockchain in IoT for healthcare applications are discussed to delineate the scope of the mentioned techniques in IoT domains. Finally, the challenges and issues of healthcare applications based on machine learning, blockchain, and IoT are discussed. The presented future directions in this domain can significantly help the scholarly community determine research gaps to address.

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STRIDE-based Cyber Security Threat Modeling for IoT-enabled Precision Agriculture Systems

Asif¹,

Hasan

Islam

et al. 2021

2021 3rd International Conference on Sustainable Technologies for Industry 4.0 (STI)

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An SDN-Enabled IoT Architecture with Fog Computing and Edge Encryption Support

Cited by 3 publications

References 25 publications

A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

Comprehensive Survey of IoT, Machine Learning, and Blockchain for Health Care Applications: A Topical Assessment for Pandemic Preparedness, Challenges, and Solutions

STRIDE-based Cyber Security Threat Modeling for IoT-enabled Precision Agriculture Systems

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