On Maximizing Quality of Information for the Internet of Things: A Real-Time Scheduling Perspective (Invited Paper)

2016 ◽  
Author(s):  
Jung-Eun Kim ◽  
Tarek Abdelzaher ◽  
Lui Sha ◽  
Amotz Bar-Noy ◽  
Reginald Hobbs ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
The Internet ◽  
Quality Of Information ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
The Internet Of Things

scholarly journals The ‘Internet of Things’ enabled real-time scheduling for remanufacturing of automobile engines

2018 ◽  
Vol 185 ◽  
pp. 562-575 ◽  
Author(s):  
Yingfeng Zhang ◽  
Sichao Liu ◽  
Yang Liu ◽  
Haidong Yang ◽  
Miao Li ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
The Internet ◽  
Real Time Scheduling ◽  
Automobile Engines ◽  
Time Scheduling ◽  
The Internet Of Things

scholarly journals An energy-aware data cleaning workflow for real-time stream processing in the internet of things

2020 ◽  
Author(s):  
Egberto Armando Rabello De Oliveira ◽  
Flávia Coimbra Delicato ◽  
Marta Lima de Queirós Mattoso
Keyword(s):  
Internet Of Things ◽  
Power Consumption ◽  
Real Time ◽  
Data Streams ◽  
Data Cleaning ◽  
Stream Processing ◽  
The Internet ◽  
Energy Aware ◽  
The Internet Of Things

The Internet of things (IoT) has recently transformed the internet, enabling the communication between every kind of objects (things). The growing number of sensors and smart devices enhanced data creation and collection capabilities and led to an explosion of generated data in the form of Data Streams. Processing these data streams is complex and presents challenges and opportunities in the stream processing field. Due to the inherent lacking of accuracy and completeness of sensor generated data, the quality of raw data is often poor. Data cleaning tasks are required to help increasing the quality of the data being processed in an IoT application. This work proposes a data stream processing workflow for IoT to be deployed at the edge of the network. It performs a fast data cleaning with low power consumption from edge and sensor nodes. The edge computing paradigm is used to bring the data cleaning task closer to the data sources and allow actions to be triggered immediately. In addition, an energy-aware data collection component is designed to reduce the network traffic and, as a consequence, decrease the power consumption of the network devices. The proposed workflow enables the deployment of long running real-time processing systems on remote outdoor environments.

scholarly journals A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2853 ◽  
Author(s):  
Berto Gomes ◽  
Luiz Muniz ◽  
Francisco da Silva e Silva ◽  
Davi dos Santos ◽  
Rafael Lopes ◽  
...  
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Quality Of Context ◽  
The Internet Of Things

scholarly journals Modelling Uptake Sensitivities of Connected and Automated Vehicle Technologies

2021 ◽  
Vol 10 (2) ◽  
pp. 88-106
Author(s):  
Gillian Harrison ◽  
Simon P. Shepherd ◽  
Haibo Chen
Keyword(s):  
Internet Of Things ◽  
Dynamic Modelling ◽  
Transport Systems ◽  
The Internet ◽  
Sensitivity Testing ◽  
Automated Vehicle ◽  
Vehicle Technologies ◽  
The Internet Of Things

Connected and automated vehicle (CAV) technologies and services are rapidly developing and have the potential to revolutionise the transport systems. However, like many innovations, the uptake pathways are uncertain. The focus of this article is on improving understanding of factors that may affect the uptake of highly and fully automated vehicles, with a particular interest in the role of the internet of things (IoT). Using system dynamic modelling, sensitivity testing towards vehicle attributes (e.g., comfort, safety, familiarity) is carried out and scenarios were developed to explore how CAV uptake can vary under different conditions based around the quality of IoT provision. Utility and poor IoT are found to have the biggest influence. Attention is then given to CAV ‘services' that are characterized by the attributes explored earlier in the paper, and it is found that they could contribute to a 20% increase in market share.

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