Neural Adaptive Transport Framework for Internetscale Interactive Media Streaming Services Network dynamics, such as bandwidth fluctuation and unexpected latency, hurt usersxe2x80x99 quality of experience (QoE) greatly for media services over the Internet. In this work, we propose a neural adaptive transport (NAT) framework to tackle the network dynamics for Internetscale interactive media services. The entire NAT system has three major components: a learning based cloud overlay routing (COR) scheme for the best delivery path to bypass the network bottlenecks while offering the minimal endtoend latency simultaneously; a residual neural network based collaborative video processing (CVP) system to trade the computational capability at clientend for QoE improvement via learned resolution scaling; and a deep reinforcement learning (DRL) based adaptive realtime streaming (ARS) strategy to select the appropriate video bitrate for maximal QoE. We have demonstrated that COR could improve the user satisfaction from 5% to 43%, CVP could reduce the bandwidth consumption more than 30% at the same quality, and DRLbased ARS can maintain the smooth streaming with u003c 50% QoE improvement, respectively.

A Congestion Avoidance for Adaptive Streaming over ICN Using Bitrate Feedback from InNetwork Nodes Adaptive streaming over information centric networking (ICN) has attracted attention as a solution to further improve quality of experience (QoE) of a viewer. In adaptive streaming over ICN, the throughput estimation in bitrate adaptation is often inaccurate. As a result, congestion occurs due to overestimate bitrate of streaming for the available bandwidth. The congestion causes a QoE degradation problem due to stall time for the vieweru0027s rebuffering. In this paper, we propose a congestion avoidance method for adaptive streaming over ICN using a feedback control of an upper limit of playing bitrate from the innetwork nodes. The proposed approach encourages early feedback to congestion by informing the upper limit of the playing bitrate to viewers from innetwork nodes detect congestion. The simulation experiment shows that the proposed method significantly improves QoE by preventing stall time due to congestion.