Computer Science Publications


Analysis of the effect of QoS on video conferencing QoE

Document Type

Conference Proceeding

Publication Date



2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019

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© 2019 IEEE. Network service providers tend to focus on the quality of service (QoS) they provide to their customers. This entails analysis of various QoS metrics (such as bandwidth, packet loss and jitter) in order to be able to improve their services. This is a single-dimensional approach to a problem that needs to be analyzed not only from a business improvement perspective but also from a customer satisfaction perspective. QoS metrics do not directly translate to customer experience, which is more qualitative than quantitative. Thus, it is necessary to correlate qualitative metrics that customers relate to with quantitative metrics that can be analyzed and improved upon by service providers. This is a non-trivial problem that needs deeper exploration. In this paper, we attempt to correlate video conferencing QoE (Quality of Experience) with network QoS. In order to do this, we developed a novel Docker image called Lime, to be able to automate the experiments and emulate the network environment. We performed 144 separate video conferences under predefined network handicaps (scenarios). We discovered that bandwidth is directly proportional to the perceived quality of the video implying that higher bandwidth is preferred. On the other hand, frequently fluctuating bandwidth quickly reduced the user-opinion, and also resulted in slower subsequent climb in opinion after a period of high fluctuation. This indicated that steady bandwidth is preferred over irregularly increasing bandwidth. Jitter and packet loss were found to contribute to negative user-opinion as well as low bandwidth. Conversely, increasing jitter and packet loss was mostly forgiven if the bandwidth stayed stable and high. Lime is shown to be a novel tool to fulfill requirements related to video conferencing experiments under pre-defined network scenarios.

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