scholarly journals A Domain-Based Access Control Mechanism Using Smart Contracts for the Internet of Things

Author(s):  
Kobaruto Sato ◽  
Masaki Bandai
2020 ◽  
Vol 174 ◽  
pp. 231-242
Author(s):  
Lihua Song ◽  
Mengchen Li ◽  
Zongke Zhu ◽  
Peng Yuan ◽  
Yunhua He

Author(s):  
Toru Homan ◽  
Masaya Morita ◽  
Yu Yamaguchi ◽  
Kazuhiro Kuwabara

This paper describes a topic database for conversation support for people with cognitive handicaps such as aphasia. The authors implemented a topic database based on word lists developed for people with aphasia as an RDF database to exploit the conceptual relationships among words and extended it to include web resources a user needs. To allow database personalization, the authors introduce an access control mechanism and incorporate the topic database into a chat system for remote conversation support over the Internet.


Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 283
Author(s):  
Fawad Ali Khan ◽  
Rafidah Md Noor ◽  
Miss Laiha Mat Kiah ◽  
Ismail Ahmedy ◽  
Mohd Yamani ◽  
...  

Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms.


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