Geodesic
Crowdsourcing Platform for QoE Evaluation for Cloud Multimedia Services
Computer Science and Information Systems, Tome 19 (2022) no. 3.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

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.
Keywords: Crowdsourcing platform, Video service, Quality of Experience (QoE), Cloud computing 
@article{CSIS_2022_19_3_a17,
     author = {Asif Ali Laghari and Hui He and Asiya Khan and Rashid Ali Laghari and Shoulin Yin and Jiachi Wang},
     title = {Crowdsourcing {Platform} for {QoE} {Evaluation} for {Cloud} {Multimedia} {Services}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {19},
     number = {3},
     year = {2022},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a17/}
}
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Asif Ali Laghari; Hui He; Asiya Khan; Rashid Ali Laghari; Shoulin Yin; Jiachi Wang. Crowdsourcing Platform for QoE Evaluation for Cloud Multimedia Services. Computer Science and Information Systems, Tome 19 (2022) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2022_19_3_a17/