LightDB: A DBMS for Virtual Reality Video
LightDB: A DBMS for Virtual Reality Video
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DOI：
10.14778/3231751.3231768
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发表时间：
2018-06
期刊：
影响因子：
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通讯作者：
Brandon Haynes;Amrita Mazumdar;Armin Alaghi;M. Balazinska;L. Ceze;Alvin Cheung
中科院分区：
文献类型：
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作者：
Brandon Haynes;Amrita Mazumdar;Armin Alaghi;M. Balazinska;L. Ceze;Alvin Cheung
我们提出了LightDB的数据模型，架构和评估，LightDB是一个数据库管理系统，旨在有效地管理虚拟，增强和混合现实（VAMR）视频内容。VAMR视频与二维视频的不同之处在于，它是具有周期性角度维度的球形，是不均匀和连续采样的，并且消费此类视频的应用通常具有苛刻的延迟和吞吐量要求。为了应对这些挑战，LightDB将VAMR视频数据视为逻辑连续的六维光场。此外，LightDB支持对光场的丰富操作集，并自动将声明性查询转换为可执行的物理计划。我们已经实现了一个原型的LightDB，并通过实验与VAMR应用在文献中，我们发现，LightDB提供了高达4倍的吞吐量的提高相比，以前的工作。
We present the data model, architecture, and evaluation of LightDB, a database management system designed to efficiently manage virtual, augmented, and mixed reality (VAMR) video content. VAMR video differs from its two-dimensional counterpart in that it is spherical with periodic angular dimensions, is nonuniformly and continuously sampled, and applications that consume such videos often have demanding latency and throughput requirements. To address these challenges, LightDB treats VAMR video data as a logically-continuous six-dimensional light field. Furthermore, LightDB supports a rich set of operations over light fields, and automatically transforms declarative queries into executable physical plans. We have implemented a prototype of LightDB and, through experiments with VAMR applications in the literature, we find that LightDB offers up to 4× throughput improvements compared with prior work.