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 774

Special Issue Editors


E-Mail Website
Guest Editor
Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan
Interests: blockchains; cloud computing; data mining; internet of things; quality of experience
Multimedia Communication and Intelligent Control, School of Engineering, Computing and Mathematics, Faculty of Science and Engineering, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
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

E-Mail Website
Guest Editor
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
Interests: image proccessing; data mining; data security; AI; remote sensing/medical image processing

E-Mail Website
Guest Editor
Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi 75660, Pakistan
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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data
  • data mining
  • cloud computing
  • Internet of Things
  • quality of experience
  • industrial IoT and big data

Published Papers

There is no accepted submissions to this special issue at this moment.
Back to TopTop