Joint Bitrate Transcoding and Parallel Cooperative Transmission Optimization for Adaptive Video Streaming in Edge Assisted Cellular Networks

The advent of online video services has resulted in a remarkable surge in Internet traffic, prompting the need for mobile edge computing (MEC) as a crucial element in augmenting the quality of adaptive streaming media services amidst the time-varying wireless channels. MEC reduces network backhaul traffic by providing video transcoding and adaptive streaming services closer to users. Nonetheless, the process of video transcoding introduces additional latency and energy consumption. In order to effectively tackle this challenge and uphold the optimal quality of experience (QoE), we propose the Joint Bitrate Transcoding and Parallel Cooperative Transmission (JBTPCT) model, which operates at the edge of mobile networks and handles multiple video chunks simultaneously. Within the JBTPCT model, the Asynchronous Advantage Actor-Critic (A3C) algorithm framework is employed to jointly account for radio access network conditions and MEC resources, leveraging a parallel execution strategy for transmission and transcoding. This integrated approach aims to minimize both latency and energy consumption while enhancing the QoE of video streaming. We evaluate the average QoE of JBTPCT in different network scenarios, and the experimental results demonstrate that JBTPCT consistently achieves higher average QoE compared to competing algorithms.