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Replicas Strategy and Cache Optimization of Video Surveillance Systems Based on Cloud Storage

机译:基于云存储的视频监控系统复制策略和缓存优化

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With the rapid development of video surveillance technology, especially the popularity of cloud-based video surveillance applications, video data begins to grow explosively. However, in the cloud-based video surveillance system, replicas occupy an amount of storage space. Also, the slow response to video playback constrains the performance of the system. In this paper, considering the characteristics of video data comprehensively, we propose a dynamic redundant replicas mechanism based on security levels that can dynamically adjust the number of replicas. Based on the location correlation between cameras, this paper also proposes a data cache strategy to improve the response speed of data reading. Experiments illustrate that: (1) our dynamic redundant replicas mechanism can save storage space while ensuring data security; (2) the cache mechanism can predict the playback behaviors of the users in advance and improve the response speed of data reading according to the location and time correlation of the front-end cameras; and (3) in terms of cloud-based video surveillance, our proposed approaches significantly outperform existing methods.
机译:随着视频监控技术的飞速发展,尤其是基于云的视频监控应用的普及,视频数据开始爆炸性增长。但是,在基于云的视频监视系统中,副本占用大量存储空间。此外,对视频播放的响应速度慢会限制系统的性能。本文综合考虑了视频数据的特点,提出了一种基于安全级别的动态冗余副本机制,可以动态调整副本数量。基于摄像机之间的位置相关性,本文还提出了一种数据缓存策略,以提高数据读取的响应速度。实验表明:(1)我们的动态冗余副本机制可以在确保数据安全性的同时节省存储空间; (2)缓存机制可以根据前端摄像机的位置和时间相关性,提前预测用户的回放行为,提高数据读取的响应速度; (3)在基于云的视频监控方面,我们提出的方法明显优于现有方法。

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