Abstract:
Fragmentation of traditional file system seriously affects storage performance.Aiming at this drawback and combined with the characteristics of content-based retrieval in video surveillance,a dedicated file system for intelligent video surveillance is proposed.The proposed approach provides an Extent-based logical volume index structure,retrieves feature content based on feature video segments,and improves index efficiency by B+ tree and bitmap.According to the index strategy proposed,recycle the oldest data based on data cluster,which realizes circular storage,optimize data block allocation policy by controlling the continuous storage time and evaluating allocated time of fragmentation,ensuring a continuous,sequential data storage.Test results show that the defragmentation impact to storage bandwidth is only 2.4%,compared with the traditional file system.It increases storage efficiency by 24.5% respectively on typical storage bit rate of 1 Mb/s,while the storage space utilization is more than 99%.
Key words:
content-based,
file system,
index strategy,
Extent structure,
defragmentation,
intelligent video surveillance
摘要： 针对传统文件系统碎片化会严重影响存储性能的问题,结合视频监控具有的基于内容检索的特点,提出一种应用于智能视频监控的专用文件系统。基于Extent的逻辑卷索引结构,以特征录像段为单位进行特征内容的索引,采用B+树和位图提高索引效率。在索引策略中,基于数据簇回收最原始数据,实现循环存储。通过控制数据连续存储的时间,优化数据块的分配,保证数据的连续、顺序存储。测试结果表明,该文件系统索引策略对存储带宽的下降比例仅为2.4%,在1 Mb/s的典型视频码率下,存储带宽相比传统文件系统提高了24.5%,存储空间利用率达到了99%。
关键词:
基于内容,
文件系统,
索引策略,
Extent结构,
碎片整理,
智能视频监控
CLC Number: