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

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