Utility Optimal Scheduling and Admission Control for Adaptive Video Streaming in Small Cell Networks

We consider the jointly optimal design of a transmission scheduling and admission control policy for adaptive video streaming over small cell networks. We formulate the problem as a dynamic network utility maximization and observe that it naturally decomposes into two subproblems: admission control and transmission scheduling. The resulting algorithms are simple and suitable for distributed implementation. The admission control decisions involve each user choosing the quality of the video chunk asked for download, based on the network congestion in its neighborhood. This form of admission control is compatible with the current video streaming technology based on the DASH protocol over TCP connections. Through simulations, we evaluate the performance of the proposed algorithm under realistic assumptions for a small-cell network.Comment: 5 pages, 4 figures. Accepted and will be presented at IEEE International Symposium on Information Theory (ISIT) 201

Adaptive Video Streaming for Wireless Networks with Multiple Users and Helpers

We consider the optimal design of a scheduling policy for adaptive video streaming in a wireless network formed by several users and helpers. A feature of such networks is that any user is typically in the range of multiple helpers. Hence, in order to cope with user-helper association, load balancing and inter-cell interference, an efficient streaming policy should allow the users to dynamically select the helper node to download from, and determine adaptively the video quality level of the download. In order to obtain a tractable formulation, we follow a "divide and conquer" approach: i) Assuming that each video packet (chunk) is delivered within its playback delay ("smooth streaming regime"), the problem is formulated as a network utility maximization (NUM), subject to queue stability, where the network utility function is a concave and componentwise non-decreasing function of the users' video quality measure. ii) We solve the NUM problem by using a Lyapunov Drift Plus Penalty approach, obtaining a scheme that naturally decomposes into two sub-policies referred to as "congestion control" (adaptive video quality and helper station selection) and "transmission scheduling" (dynamic allocation of the helper-user physical layer transmission rates).Our solution is provably optimal with respect to the proposed NUM problem, in a strong per-sample path sense. iii) Finally, we propose a method to adaptively estimate the maximum queuing delays, such that each user can calculate its pre-buffering and re-buffering time in order to cope with the fluctuations of the queuing delays. Through simulations, we evaluate the performance of the proposed algorithm under realistic assumptions of a network with densely deployed helper nodes, and demonstrate the per-sample path optimality of the proposed solution by considering a non-stationary non-ergodic scenario with user mobility, VBR video coding.Comment: final version to appear in IEEE Transactions on Communication