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A framework for scalable cloud video recorder system in surveillance environment 2012 9th International Conference on Ubiquitous Intelligence and Computing.

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Presentation on theme: "A framework for scalable cloud video recorder system in surveillance environment 2012 9th International Conference on Ubiquitous Intelligence and Computing."— Presentation transcript:

1 A framework for scalable cloud video recorder system in surveillance environment 2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing Speaker: 劉源蔁

2 Introduction

3 Evolution for IP based Video Survellance The codec, H.264 could even make over one hundred compression ratio for video data

4 Trend from DVR to NVR 部署規劃 與 擴充延展 佈線 隨插即用 超高清畫質錄影 錄影儲存

5 Hybrid DVR/NVR

6 Trend From NVR to CVR Most deployment architecture for large scale video recording solution are fix connection model. Each NVR responsible for 64 camera sources, and ten NVR can support 640 camera sources.

7 Fix connection NVR environment

8 Cloud computing and Virtualization

9 Video Surveillance Build a central cluster for large wide area, large scale camera network in campus under Hadoop distributed file system.

10 Existing Video Recording systems Currently, high level hardware based network based video recorder device may support 64 channels of concurrent streaming source. Geovision’s IP surveillance software and NUUO’s Central Management System.

11 Scenario for Cloud Video Recorder System

12 System Architecture Virtualization Stream Collector Streaming Server Hadoop File System Policy controller Intelligent Analysis Web server

13

14 Deployment design for Public cloud

15 Deployment design for Private/hybrid cloud

16 EXPERIMENT DESIGN &DISCUSSION Experiment setup Bandwidth usage Backup issue Video Analysis using Mapreduce technology User monitoring

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18 Backup issue

19 Video Analysis using Map Reduce technology

20 User monitoring Real time Transcending Streaming technology

21 CONCLUSION AND FUTURE WORKS More experiments in proposed system, such as deploy one thousand real time source and observe its outcome. Intelligent and Real-time Motion detection: apply Map/Reduce framework to make real time patent recognition using replica data on backup node.


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