scholarly journals Internet of Things-Aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 62962-63003 ◽  
Author(s):  
Yasir Saleem ◽  
Noel Crespi ◽  
Mubashir Husain Rehmani ◽  
Rebecca Copeland
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions

scholarly journals Internet of Things (IoT) Operating Systems Management: Opportunities, Challenges, and Solution

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1793 ◽  
Author(s):  
Yousaf Bin Zikria ◽  
Sung Won Kim ◽  
Oliver Hahm ◽  
Muhammad Khalil Afzal ◽  
Mohammed Y. Aalsalem
Keyword(s):  
Internet Of Things ◽  
Low Cost ◽  
Future Research ◽  
Technological Innovations ◽  
Special Issue ◽  
Research Directions ◽  
Key Factor ◽  
Future Research Directions ◽  
Standard Set

Internet of Things (IoT) is rapidly growing and contributing drastically to improve the quality of life. Immense technological innovations and growth is a key factor in IoT advancements. Readily available low cost IoT hardware is essential for continuous adaptation of IoT. Advancements in IoT Operating System (OS) to support these newly developed IoT hardware along with the recent standards and techniques for all the communication layers are the way forward. The variety of IoT OS availability demands to support interoperability that requires to follow standard set of rules for development and protocol functionalities to support heterogeneous deployment scenarios. IoT requires to be intelligent to self-adapt according to the network conditions. In this paper, we present brief overview of different IoT OSs, supported hardware, and future research directions. Therein, we provide overview of the accepted papers in our Special Issue on IoT OS management: opportunities, challenges, and solution. Finally, we conclude the manuscript.

scholarly journals Application of Blockchain for Internet of Things: A Bibliometric Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ruijun Duan ◽  
Li Guo
Keyword(s):  
Internet Of Things ◽  
Business Models ◽  
Citation Index ◽  
Security Requirements ◽  
Future Research ◽  
Privacy And Security ◽  
Bibliometric Method ◽  
Research Directions ◽  
Security Issues ◽  
Future Research Directions

As a disruptive emerging technology, the Internet of things (IoT) has rapidly developed, but its privacy risks and security vulnerabilities are still key challenges. The decentralized and distributed architecture of blockchain has the potential to satisfy IoT privacy and security requirements. This gives birth to the new domain of blockchain for IoT (BIoT). BIoT will cause significant transformations across several industries, paving the way for new business models. Based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) databases in Web of Science (WoS) Core Collection, this study aims to explore the research trends and cooperation in the field of BIoT using the bibliometric method. The results indicate that the publications in this field have increased significantly from 2016 to 2020, with China and the USA being the most productive and influential countries. Keyword co-occurrence analysis shows that the most important research topics are as follows: security issues, core technologies, application dimensions, and transaction processes. Text mining analysis indicates that future research directions for BloT will focus more on both computing paradigms and key applications. This study will provide researchers with a greater understanding on the state of the art of BIoT and will serve as a reference for researchers engaging in this field to identify their own future research directions.

scholarly journals Defensive Signal Processing: The Case for the Use of Nonparametric and Robust Statistical Methods to Reduce Product Liability Exposure

2017 ◽  
Author(s):  
Michael Lang
Keyword(s):  
Signal Processing ◽  
Internet Of Things ◽  
Academic Research ◽  
Product Liability ◽  
Physical World ◽  
Legal Aspects ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
Robust Statistical Methods

This paper makes the case that in an Internet of Things (IoT) world where data processing hasbecome pervasive, the assessment of whether or not the underlying (statistical) modeling assumptions are justified and appropriate should no longer be limited to the perspective of mathematical statistics alone. The paper argues that large parts of sound academic research in engineering lack practical merit in that, akin to a concept car, they are not market-ready, most commonly due to feasibility and liability issues. Through an analysis of both statistical and legal aspects it will be shown that the stoic pursuit of ‘optimality’ more often than not yields to risky and suboptimal outcomes when applied to actual physical world problems. To address this, the concept of ‘Defensive Signal Processing’ is introduced and future research directions are brieflyoutlined.

Recent advances on reliability evaluation and optimization of linear multistate consecutively connected systems

2020 ◽  
Vol 14 ◽  
Author(s):  
Li Qu ◽  
Chenjing Han ◽  
Yingchun Li ◽  
Kaiye Gao ◽  
Rui Peng
Keyword(s):  
Internet Of Things ◽  
Optimal System ◽  
Future Research ◽  
Research Directions ◽  
Telecommunication Systems ◽  
Multistate System ◽  
Different Types ◽  
Future Research Directions ◽  
Practical Factors ◽  
System Configurations

: With the progress of technology, the model of linear multistate consecutively connected systems (LMCCS) is applied more and more widely, such as telecommunication systems, internet of things, etc. LMCCS contains a series of linearly arranged nodes and any disconnection between nodes will lead to the failure of the whole system. Thus, the reliability of a linear multistate system is affected by many factors such as the positioning of elements. In order to be able to incorporate different types of complicated practical factors, researchers have proposed different extensions for LMCCS model. Besides, models are proposed to study the optimal system configurations of such systems considering reliability and some other objectives or constraints. Facing amounts of works on LMCCS, this paper aims to review these literatures, classify them, and elicit some future research directions.

scholarly journals Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

2021 ◽  
Vol 11 (12) ◽  
pp. 5713
Author(s):  
Majda Wazzan ◽  
Daniyal Algazzawi ◽  
Omaima Bamasaq ◽  
Aiiad Albeshri ◽  
Li Cheng
Keyword(s):  
Internet Of Things ◽  
Detection Methods ◽  
Future Research ◽  
Research Papers ◽  
Botnet Detection ◽  
Research Directions ◽  
Malicious Activity ◽  
Research Procedure ◽  
Future Research Directions ◽  
Iot Devices

Internet of Things (IoT) is promising technology that brings tremendous benefits if used optimally. At the same time, it has resulted in an increase in cybersecurity risks due to the lack of security for IoT devices. IoT botnets, for instance, have become a critical threat; however, systematic and comprehensive studies analyzing the importance of botnet detection methods are limited in the IoT environment. Thus, this study aimed to identify, assess and provide a thoroughly review of experimental works on the research relevant to the detection of IoT botnets. To accomplish this goal, a systematic literature review (SLR), an effective method, was applied for gathering and critically reviewing research papers. This work employed three research questions on the detection methods used to detect IoT botnets, the botnet phases and the different malicious activity scenarios. The authors analyzed the nominated research and the key methods related to them. The detection methods have been classified based on the techniques used, and the authors investigated the botnet phases during which detection is accomplished. This research procedure was used to create a source of foundational knowledge of IoT botnet detection methods. As a result of this study, the authors analyzed the current research gaps and suggest future research directions.

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