Duration-Squeezing-Aware Communication and Computing for Proactive VR

TL;DR

This paper proposes a duration-squeezing-aware optimization framework for proactive VR streaming that ensures sufficient time for communication and computing tasks, improving task completion rates under resource constraints.

Contribution

It introduces a novel joint optimization method that accounts for duration squeezing constraints, deriving closed-form solutions and identifying resource tradeoff regions.

Findings

Optimal resource allocation depends on total proactive task duration.

Prohibiting duration squeezing affects the effectiveness of resource increases.

Three distinct resource tradeoff regions are identified and validated.

Abstract

Proactive tile-based virtual reality video streaming computes and delivers the predicted tiles to be requested before playback. All existing works overlook the important fact that computing and communication (CC) tasks for a segment may squeeze the time for the tasks for the next segment, which will cause less and less available time for the latter segments. In this paper, we jointly optimize the durations for CC tasks to maximize the completion rate of CC tasks under the task duration-squeezing-aware constraint. To ensure the latter segments remain enough time for the tasks, the CC tasks for a segment are not allowed to squeeze the time for computing and delivering the subsequent segment. We find the closed-form optimal solution, from which we find a minimum-resource-limited, an unconditional and a conditional resource-tradeoff regions, which are determined by the total time for proactive CC tasks and the playback duration of a segment. Owing to the duration-squeezing-prohibited constraints, the increase of the configured resources may not be always useful for improving the completion rate of CC tasks. Numerical results validate the impact of the duration-squeezing-prohibited constraints and illustrate the three regions.