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Nowadays, video streaming has become one of the most dominant services due to increasing interest in watching online television programs and video-on-demand activities. Providing this service requires high quality, high speed and high-capacity network infrastructures. In this work, we propose a data-drivenbased fuzzy logic inference algorithm for quality of experience (QoE) modeling of video streaming services in Addis Ababa City LTE network. The proposed fuzzy logic inference system model is used to measure the user perception from the key quality of indicator (KQI) parameters. The model is essential to replace conventional subjective measurement techniques that are costly and inefficient. In addition, the proposed fuzzy logic inference system model is helpful for business decision making, network planning and optimization activities. To analyze the performance of the proposed model, we consider main KQI parameters such as video streaming start success rate, video streaming start delay, video streaming play disconnection rate, video streaming stall frequency and video streaming stalled time rate. We perform numerical simulation to analyze the proposed model and to validate the impacts of main KQI parameters on the quality of experience in LTE video streaming services. The simulation results show that video streaming stall frequency and video streaming start delay rate play a major impact on user perception by 33% and 25%, respectively. Besides, validation of the results shows that the proposed fuzzy logic inference system model is accurate, consistent and linear compared to currently existing models. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Multi-Constraint Quality-of-Experience (QoE) centric Routing (MCQR) technique for efficient real-time video streaming over Mobile Ad-hoc Networks (MANETs). The dynamic estimation of link quality metric during MCQR route discovery process is the key of enhancing QoE at end user. MCQR limits end-to-end delay and jitter of received data packets by selecting long lifetime routes with maximum permissible delay. This minimizes the distortion caused fluctuations in perceived video. To prove the effectiveness of MCQR for real-time video streaming, we have designed a hybrid MANET consisting of simulated nodes and physical machines. In our hybrid network, the source and destination nodes are video traffic generators and receivers running on physical devices. Emulation results are obtained using real-time video streaming over high fidelity virtual wireless network, and conforming that the MCQR protocol provides satisfactory QoE to end users as compared to existing similar techniques. The packet delivery ratio of MCQR is higher than 90 % and its mean opinion score is higher than three (i.e., satisfactory) even when mobility and shadowing effects are kept high in target network scenarios. These improvements are achieved along with still maintaining similar or better routing overhead and processing delays. [ABSTRACT FROM AUTHOR]

Highlights: [•] Subjective quality assessments for video streaming over tablet devices. [•] Parametric quality model useful for system control and optimization. [•] Comparison of with alternative subjective assessment results and models. [ABSTRACT FROM AUTHOR]