Emergent Mind

Optimal Decentralized Dynamic Policies for Video Streaming over Wireless Channels

(1902.07418)
Published Feb 20, 2019 in cs.NI and math.OC

Abstract

The problem addressed is that of optimally controlling, in a decentralized fashion, the download of mobile video, which is expected to comprise 75 % of total mobile data traffic by 2020. The server can dynamically choose which packets to download to clients, from among several packets which encode their videos at different resolutions, as well as the power levels of their transmissions. This allows it to control packet delivery probabilities, and thereby, for example, avert imminent video outages at clients. It must however respect the access point's constraints on bandwidth and average transmission power. The goal is to maximize video "Quality of Experience" (QoE), which depends on several factors such as (i) outage duration when the video playback buffer is empty, (ii) number of outage periods, (iii) how many frames downloaded are of lower resolution, (iv) temporal variations in resolution, etc. It is shown that there exists an optimal decentralized solution where the AP announces the price of energy, and each client distributedly and dynamically maximizes its own QoE subject to the cost of energy. A distributed iterative algorithm to solve for optimal decentralized policy is also presented. Further, for the client-level QoE optimization, the optimal choice of video-resolution and power-level of packet transmissions has a simple monotonicity and threshold structure vis-a-vis video playback buffer level. When the number of orthogonal channels is less than the number of clients, there is an index policy for prioritizing packet transmissions. When the AP has to simply choose which clients' packets to transmit, the index policy is asymptotically optimal as the number of channels is scaled up with clients.

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