Startup Delay Aware Short Video Ordering: Problem, Model, and A Reinforcement Learning based Algorithm

TL;DR

This paper addresses reducing startup delays in short video streaming by optimizing video order using a reinforcement learning algorithm, improving user experience and network efficiency.

Contribution

It formulates the video ordering problem as an NP-hard combinatorial optimization and proposes a novel PSAC reinforcement learning algorithm to solve it effectively.

Findings

PSAC significantly reduces startup delay compared to baselines.

The problem is proven NP-hard, highlighting its complexity.

Numerical results validate the effectiveness of the proposed approach.

Abstract

Short video applications have attracted billions of users on the Internet and can satisfy diverse users' fragmented spare time with content-rich and duration-short videos. To achieve fast playback at user side, existing short video systems typically enforce burst transmission of initial segment of each video when being requested for improved quality of user experiences. However, such a way of burst transmissions can cause unexpected large startup delays at user side. This is because users may frequently switch videos when sequentially watching a list of short videos recommended by the server side, which can cause excessive burst transmissions of initial segments of different short videos and thus quickly deplete the network transmission capacity. In this paper, we adopt token bucket to characterize the video transmission path between video server and each user, and accordingly study how to effectively reduce the startup delay of short videos by effectively arranging the viewing order of a video list at the server side. We formulate the optimal video ordering problem for minimizing the maximum video startup delay as a combinatorial optimization problem and prove its NP-hardness. We accordingly propose a Partially Shared Actor Critic reinforcement learning algorithm (PSAC) to learn optimized video ordering strategy. Numerical results based on a real dataset provided by a large-scale short video service provider demonstrate that the proposed PSAC algorithm can significantly reduce the video startup delay compared to baseline algorithms.