ORCID
- Khan, Asiya: 0000-0003-3620-3048
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.
DOI
10.2298/csis220322038l
Publication Date
2022-07-01
Publication Title
Computer Science and Information Systems
Volume
19
Issue
3
ISSN
1820-0214
Embargo Period
2022-11-05
Organisational Unit
School of Engineering, Computing and Mathematics
First Page
1305
Last Page
1328
Recommended Citation
Laghari, A., He, H., Khan, A., Laghari, R., Yin, S., & Wang, J. (2022) 'Crowdsourcing platform for QoE evaluation for cloud multimedia services', Computer Science and Information Systems, 19(3), pp. 1305-1328. Available at: https://doi.org/10.2298/csis220322038l