Crowdsourcing Platform for QoE Evaluation for Cloud Multimedia Services

Asif Ali Laghari1, Hui He2, Asiya Khan3, Rashid Ali Laghari4, Shoulin Yin5 and Jiachi Wang6

  1. Department of Computer Science, Sindh Madressatul Islam University
    Karachi, Pakistan
  2. School of Computer Sciencee & Technology, Harbin Institute of Technology
    Harbin, China
  3. School of Engineering, University of Plymouth
    United Kingdom
  4. Mechanical Engineering Department, King Fahd University of Petroleum and Minerals
    Dhahran 31261, Saudi Arabia
  5. School of Information and Communication Engineering, Harbin Engineering University
    Harbin China
  6. Software College, Shenyang Normal University
    Shenyang 110034, China


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)

Publication information

Volume 19, Issue 3 (September 2022)
Year of Publication: 2022
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable 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),