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Implementation and Evaluation of Large-Scale Video Surveillance System Based on P2P Architecture and Cloud Computing

机译:基于P2P架构和云计算的大型视频监控系统的实现与评估

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Video surveillance system (VSS) is increasingly becoming important part in daily life. For traditional VSS, each camera stores streaming data to a centralized server. It will create a great volume of video data for a large VSS and may raise some issues in keeping daily video data to centralized server, such as limited bandwidth and storage insufficiency of server and lower reliability and scalability. In order to solve the problem, we have proposed an architecture for VSS based on well-developed peer-to-peer technique and emerging cloud computing. In this paper, we implement a large-scale VSS (LVSS) and propose an evaluation framework based on the proposed architecture. We implement the LVSS exploits inherent characteristics of P2P and cloud computing to provide an economic, scalable, reliable, and efficient approach to store streaming video. We conducted some experiments to evaluate effectiveness and efficiency of the system. The result shows that the proposed architecture outperforms traditional VSS in terms of effectiveness, efficiency, reliability, and scalability.
机译:视频监控系统(VSS)日益成为日常生活中的重要组成部分。对于传统的VSS,每个摄像机都将流数据存储到中央服务器。它将为大型VSS创建大量视频数据,并可能在将日常视频数据保存到集中式服务器时引发一些问题,例如带宽有限,服务器存储不足以及可靠性和可伸缩性较低。为了解决该问题,我们提出了一种基于成熟的对等技术和新兴的云计算的VSS体系结构。在本文中,我们实现了大型VSS(LVSS),并基于所提出的体系结构提出了一个评估框架。我们实施LVSS利用P2P和云计算的固有特性,以提供一种经济,可扩展,可靠和高效的方法来存储流视频。我们进行了一些实验,以评估系统的有效性和效率。结果表明,所提出的体系结构在有效性,效率,可靠性和可扩展性方面优于传统的VSS。

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