An Adaptive Video Quality and Optimization with Enhanced Streaming Taxonomy (AVQOES)

The AVQOES taxonomy, denoting "Adaptive Video Quality and Optimization with Enhanced Streaming," presents a comprehensive and structured framework for organizing mathematical optimization techniques applied in adaptive video streaming systems. As digital video consumption becomes increasingly ubiquitous, ensuring a seamless, high-quality viewing experience is essential. This taxonomy acknowledges the intricacies of adaptive streaming, including rate-distortion optimization, quality of experience (QoE) optimization, and throughput maximization. It covers a spectrum of optimization algorithms, adaptation variables, and constraints. Moreover, it integrates quality metrics such as PSNR, SSIM, VMAF, and both quality of experience (QoE) and quality of service (QoS) metrics, incorporating bandwidth and buffer levels. This framework discerns between client-based, in-networkbased, and server-based optimization strategies, each offering distinct advantages and constraints. Furthermore, the AVQOES taxonomy expands to include Bayesian Optimization, enriching the array of techniques available for addressing intricate, non-convex problems in the realm of adaptive video streaming. By providing this organized framework, the taxonomy empowers system designers to make informed choices, facilitating the creation of adaptive video streaming solutions that enhance the user experience, ensuring highquality content delivery in diverse network conditions and across an array of devices.