Crowdsourcing Platform for QoE Evaluation for Cloud Multimedia Services
- Department of Computer Science, Sindh Madressatul Islam University
Karachi, Pakistan
asif.laghari@smiu.edu.pk - School of Computer Sciencee & Technology, Harbin Institute of Technology
Harbin, China
hehui@hit.edu.cn - School of Engineering, University of Plymouth
United Kingdom
asiya.khan@plymouth.ac.uk - Mechanical Engineering Department, King Fahd University of Petroleum and Minerals
Dhahran 31261, Saudi Arabia
rashidalilaghari@gmail.com - School of Information and Communication Engineering, Harbin Engineering University
Harbin China
352720214@qq.com - Software College, Shenyang Normal University
Shenyang 110034, China
853757309@qq.com
Abstract
This paper presents a novel web-based crowdsourcing platform for the assessment of the subjective and objective quality of experience (QoE) of the video service in the cloud-server environment. The user has the option to enter subjective QoE data for video service by filling out a web questionnaire. The objective QoE data of the cloud-server, network condition, and the user device is automatically captured by the crowdsourcing platform. Our proposed system collects both objective and subjective QoE simultaneously in real-time. The paper presents the key technologies used in the development of the platform and describes the functional requirements and design ideas of the system in detail. The system collects real-time comprehensive data to enhance the quality of the user experience to provide a valuable reference. The system is tested in a real-time environment and the test results are given in terms of the system performance. The crowdsourcing platform has new features of real-time network monitoring, the client device, and cloud monitoring, which currently has not been provided by existing web platforms and crowdsourcing frameworks. The results show that 1MB buffer is filled 100% very soon after starting watching videos from the crowdsourcing platform.
Key words
Crowdsourcing platform, Video service, Quality of Experience (QoE), Cloud computing
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS220322038L
Publication information
Volume 19, Issue 3 (September 2022)
Year of Publication: 2022
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
Portable Document Format
How to cite
Laghari, A. A., He, H., Khan, A., Laghari, R. A., Yin, S., Wang, J.: Crowdsourcing Platform for QoE Evaluation for Cloud Multimedia Services. Computer Science and Information Systems, Vol. 19, No. 3, 1305-1328. (2022), https://doi.org/10.2298/CSIS220322038L