Enhancing Mobile Video Streaming through AMES-Cloud: A Cloud Computing Approach to Addressing Wireless Link Challenges

Despite extensive efforts by network operators to enhance wireless connectivity (such as 5G and LTE), the surging demand for mobile video content is rapidly surpassing the capacity of wireless links. As video file movement over communication systems continues to rise, the existing connection capacity struggles to retain pace, leading to poor service quality, including long buffering times and intermittent disruptions. This study offers AMES-Cloud, an adaptive communication systems video running and allocating platform, in response to this difficulty. AMES-Cloud archives videos effectively and is utilized in cloud computing to develop isolated agents for specific mobile users. By utilising Scalable Video Coding algorithms, these agents can adapt to changing link quality and provide uninterrupted video streaming. Furthermore, by employing background pushing features across several components, including VB, subVBs, and localVB AMES-Cloud hopes to offer mobile consumers smooth video streaming experiences. Through a prototype implementation and evaluation, AMES-Cloud demonstrates significant improvements in mobile streaming adaptability, leveraging cloud computing techniques. It's important to note that the cost of encoding workload in the cloud was not considered during the prototype implementation.