Big Data Analytics in Quality of Experience
A special issue of Data (ISSN 2306-5729). This special issue belongs to the section "Information Systems and Data Management".
Deadline for manuscript submissions: closed (1 March 2024) | Viewed by 908
Special Issue Editors
Interests: blockchains; cloud computing; data mining; internet of things; quality of experience
Interests: prediction and control of video quality using AI, ML, cloud computing, fuzzy logic, applying computer vision techniques, and deep learning in pedestrian recognition; disease identification in cotton crops and damage recognition in wind turbines
Special Issues, Collections and Topics in MDPI journals
Interests: image proccessing; data mining; data security; AI; remote sensing/medical image processing
Interests: Machine Learning; Neural Networks and Artificial Intelligence; Computer Vision; Image Processing; Machine Intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
IoT sensors and other computing devices generate a significant amount of data, which are stored in the cloud in the shape of big data. These data may be images, videos, and user feedback about the services and products. Quality of experience is based on data about the user’s feedback and comments about the services. Currently, industrial IoT development is based on the user’s requirement (QoE), and IoT-based smart devices generate data about user mistakes, application software errors, and the submission of user reports. Millions of smart devices and users submit data to industries and store them in huge amounts on the cloud. This big data contains positive/negative, cultural/genre and type of data, and errors of application and hardware. The accuracy of data mining is still a challenge, as is the ability for a developer to obtain accurate and positive data from big data for future development.
This Special Issue aims to publish high-quality papers that extend the current state of the art with innovative ideas and solutions in the broad area of big data activities for quality of service and better quality of experience. Contributions may present and solve open research problems, integrate efficient novel solutions, present performance evaluations, and compare new methods with existing solutions. Theoretical as well as experimental studies for typical and newly emerging convergence technologies and use cases enabled by recent advances are encouraged. High-quality review papers are also welcome.
Potential topics include, but are not limited to the following:
- QoE/QoS in big data applications;
- QoE/QoS for big data processing;
- QoE/QoS in cloud/fog/edge computing for big data storage and transfer;
- QoE/QoS for big data management;
- User preferences models for big data collection;
- Machine/deep learning and QoE for big data;
- New methods/models for QoE assessment for big data;
- QoE of IoT big data;
- Industrial IoT and big data;
- QoE for big data of cloud multimedia and gaming.
Dr. Asif Ali Laghari
Dr. Asiya Khan
Dr. Shoulin Yin
Dr. Abdullah Ayub Khan
Guest Editors
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Keywords
- big data
- data mining
- cloud computing
- Internet of Things
- quality of experience
- industrial IoT and big data
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