QoE Estimation Model for a Secure Real-Time Voice Communication System in the Cloud

As moving towards cloud-based real-time services, we are witnessing the shift from a technology-driven services to service provisioning paradigms, that is, from Quality of Service (QoS) to Quality of Experience (QoE). User experience and satisfaction are placed at the epicenter of the system design. QoE is a measurement of user experience on the provided service by a system. Often QoE is measured by subjective mechanisms, such as user experience surveys and mean opinion scores (MOS) methods, which can be a costly and time-consuming process. Using an adequate QoE model to measure user experience of perceived quality is cost-effective, compared to using time-consuming subjective surveys. Applying an adequate QoE model to assess user experience is advantageous for cloud-based real-time services such as voice and video. This study uses a formula-based QoE estimation model to estimate and predict QoE prior to the deployment or during the planning stage of the system service. This study investigates a real-world scenario of a company that recently moved to its premises-based real-time trading communication system (TCS) to a public cloud. A simulation system using OPNET is also implemented to illustrate the usefulness of the model. Our result shows that the effect of delay on the users experience of the service provided by the cloud-based TCS is minimum comparing to packet loss rate (PLR) and Jitter. However, it has been observed that the overhead of the different security settings of the TCS system had no major negative impact to the user experience. The proposed model can be used as a QoE control mechanism and network optimization for cloud-based TCS services.