Implementation and Evaluation of Large-Scale Video Surveillance System Based on P2P Architecture and Cloud Computing. (15th April 2014)

• Record Type: Journal Article
• Authors: Lo, Win-Tsung; Chang, Yue Shan; Sheu, Ruey-Kai; Yang, Chao-Tung; Juang, Tong-Ying; Wu, Yu-Sheng
• Other Names: Jung Jason J. Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2014)
• Publication Date: 2014-04-15
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2014/375871
• Languages: English
• ISSNs: 1550-1329

Abstract

Abstract : 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.