Omnidirectional applications are immersive and highly interactive, which can improve the efficiency of remote collaborative work among factory workers. The transmission of omnidirectional video (OV) is the most important step in implementing virtual remote collaboration. Compared with the ordinary video transmission, OV transmission requires more bandwidth, which is still a huge burden even under 5G networks. The tile-based scheme can reduce bandwidth consumption. However, it neither accurately obtain the field of view(FOV) area, nor difficult to support real-time OV streaming. In this paper, we propose an edge-assisted viewport adaptive scheme (EVAS-OV) to reduce bandwidth consumption during real-time OV transmission. First, EVAS-OV uses a Gated Recurrent Unit(GRU) model to predict users' viewport. Then, users were divided into multicast clusters thereby further reducing the consumption of computing resources. EVAS-OV reprojects OV frames to accurately obtain users' FOV area from pixel level and adopt a redundant strategy to reduce the impact of viewport prediction errors. All computing tasks were offloaded to edge servers to reduce the transmission delay and improve bandwidth utilization. Experimental results show that EVAS-OV can save more than 60\% of bandwidth compared with the non-viewport adaptive scheme. Compared to a two-layer scheme with viewport adaptive, EVAS-OV still saves 30\% of bandwidth.

中文翻译：

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用于实时全向视频传输的边缘辅助视口自适应方案

全方位应用具有沉浸感和高度交互性，可以提高工厂工人之间远程协作工作的效率。全向视频（OV）的传输是实现虚拟远程协作最重要的一步。与普通视频传输相比，OV传输需要更多的带宽，即使在5G网络下，这仍然是一个巨大的负担。基于区块的方案可以减少带宽消耗。然而，它既不能准确获取视场（FOV）区域，也难以支持实时 OV 流媒体。在本文中，我们提出了一种边缘辅助视口自适应方案（EVAS-OV），以减少实时 OV 传输过程中的带宽消耗。首先，EVAS-OV 使用门控循环单元（GRU）模型来预测用户的视口。然后，用户被分成组播集群，从而进一步减少计算资源的消耗。EVAS-OV重新投影OV帧，从像素级准确获取用户的FOV区域，并采用冗余策略减少视口预测误差的影响。所有计算任务都卸载到边缘服务器，以减少传输延迟并提高带宽利用率。实验结果表明，与非视口自适应方案相比，EVAS-OV可以节省60%以上的带宽。与具有视口自适应的两层方案相比，EVAS-OV 仍然节省了 30% 的带宽。所有计算任务都卸载到边缘服务器，以减少传输延迟并提高带宽利用率。实验结果表明，与非视口自适应方案相比，EVAS-OV可以节省60%以上的带宽。与具有视口自适应的两层方案相比，EVAS-OV 仍然节省了 30% 的带宽。所有计算任务都卸载到边缘服务器，以减少传输延迟并提高带宽利用率。实验结果表明，与非视口自适应方案相比，EVAS-OV可以节省60%以上的带宽。与具有视口自适应的两层方案相比，EVAS-OV 仍然节省了 30% 的带宽。