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

Abstract

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.

Cache Performance Optimization of QoC Framework

“…Cache layer composed of two parts, one composed of multiple Memcached distributed cache server composed of cache acceleration layer and back-end database query structure cache which reduces the load on the database. The other part is the multi-content cache, the server composed of the contents of the cache layer and the content server in the video file cache, the content server load to more than one server to meet the purpose of load balancing [15,16].…”