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Multimedia Big Data Frame Combination Storage Strategy Based on Virtual Space Distortion

机译:基于虚拟空间失真的多媒体大数据帧组合存储策略

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摘要

Aiming at the transmission reliability and storage management of multimedia data, the multimedia big data frame combination storage strategy is proposed based on the virtual space distortion analysis model. On the one hand, the virtual space distortion analysis model is established. This model can be used to find the high similarity of video frames and flow structures in different multimedia streams. The model can be used to uniform the multimedia stream state and effectively improve the efficiency of data mining. The model can effectively analyze the difference between the multimedia stream of virtual space and the storage of the server group. On the other hand, based on the distorted efforts of the virtual space and heterogeneous of the multimedia data stream, combined with big data multimedia service requirements, the big data frame combination of storage space and virtual space integration would be integrated as a whole through the multimedia data frame combination and distorted perception. Finally, the combination of multimedia data frames is proposed. The delay, channel, storage and big data processing level of the virtual space storage scheme and were analyzed and evaluated by the simulation experiment, compared with the physical storage scheme of the multimedia big data. The experimental results show that the proposed scheme has significant advantages in the above aspects.
机译:针对多媒体数据的传输可靠性和存储管理,提出了基于虚拟空间失真分析模型的多媒体大数据帧组合存储策略。一方面,建立了虚拟空间畸变分析模型。该模型可用于发现不同多媒体流中视频帧和流结构的高度相似性。该模型可用于统一多媒体流状态,有效提高数据挖掘效率。该模型可以有效地分析虚拟空间的多媒体流与服务器组存储之间的差异。另一方面,基于虚拟空间扭曲的工作和多媒体数据流的异构性,结合大数据多媒体服务需求,将存储空间和虚拟空间集成的大数据帧组合通过多媒体数据帧组合和失真的感知。最后,提出了多媒体数据帧的组合。通过仿真实验对虚拟空间存储方案的时延,通道,存储和大数据处理水平进行了分析和评估,并与多媒体大数据的物理存储方案进行了比较。实验结果表明,该方案在上述方面具有明显的优势。

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