Optimizing the Viewer Experience: A Review of Multi-Objective Optimization Models in Adaptive Video Streaming

As the demand for high-quality video content continues to surge across diverse network conditions, adaptive video streaming has emerged as a critical technology. This paper delves into the realm of adaptive video streaming, with a specific focus on addressing the inherent trade-offs through multi-objective optimization. We investigate mathematical models designed to simultaneously optimize conflicting objectives, such as minimizing rebuffering events and maximizing video quality. The paper surveys the landscape of adaptive streaming technologies, protocols, and key quality metrics, providing a comprehensive background. The core of the review explores various mathematical models employed for multiobjective optimization in adaptive streaming, shedding light on the intricacies of balancing competing goals. Case studies and implementations are scrutinized to showcase practical applications, and challenges in the field are identified, underscoring the dynamic nature of network conditions and user preferences. The review concludes with insights into future directions, urging continued research to enhance the performance of adaptive streaming systems and ensure an optimal viewer experience