Feasibility Study of Stochastic Streaming with 4K UHD Video Traces

TL;DR

This study evaluates the effectiveness of stochastic streaming algorithms using current 4K UHD video traces, demonstrating their superiority over queue-independent methods in maintaining streaming quality.

Contribution

It provides the first assessment of stochastic streaming algorithms with 4K UHD video traces, confirming their improved performance over traditional queue-independent approaches.

Findings

Stochastic algorithms outperform queue-independent methods.

Performance gains are verified with 4K UHD video traces.

The study confirms the feasibility of stochastic streaming for high-resolution videos.

Abstract

This paper performs the feasibility study of stochastic video streaming algorithms with up-to-date 4K ultra-high-definition (UHD) video traces. In previous work, various stochastic video streaming algorithms were proposed which maximize time-average video streaming quality subject to queue stability based on the information of queue-backlog length. The performance improvements with the stochastic video streaming algorithms were verified with traditional MPEG test sequences; but there is no study how much the proposed stochastic algorithm is better when we consider up-to-date 4K UHD video traces. Therefore, this paper evaluates the stochastic streaming algorithms with 4K UHD video traces; and verifies that the stochastic algorithms perform better than queue-independent algorithms, as desired.