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The Design and Implementation of a Dashboard Web-Based Video Surveillance in OpenStack Swift

机译:OpenStack Swift中仪表板基于网络视频监控的设计与实现

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The purpose aims at deploying a fully functional OpenStack cluster with different settings and operational environments, followed by an in-depth analysis of its network performance and explanation of what happens behind the scene. Where OpenStack Virtual Machines perform these services for data storage files are stored in an authenticated cloud storage service center. The methodology used presents various scenarios using OpenStack Virtual machines and cloud-based to improve network performance video surveillance backend system architecture is developed with the Sensor web Enablement framework and cloud-based data storage. Data is obtained through simulators on camera/edge devices, file and metadata sharing, and fast cloud base storage. This study aims to compare the performance load resulting from large-scale video surveillance with small ones to show satisfactory performance, scalability, and good reliability from cloud-based storage systems for smart MCS. The most important feature is storage is adjusted dynamically, and there won’t be any worry about space being inadequate or wasted. This paper presents a solution for deploying web applications for CCTV video surveillance, an object cloud storage service system based on the open-source cloud operating system OpenStack Swift. It’s working in the OpenStack swift on IaaS and allocates resources for storage original data by multiple camera surveillance (MCS).
机译:目的旨在部署具有不同设置和操作环境的全功能OpenStack集群,然后深入分析其网络性能和对场景后面发生的事情的解释。其中OpenStack虚拟机执行这些服务的数据存储文件存储在经过身份验证的云存储服务中心。使用的方法使用OpenStack虚拟机提供了各种场景,并以云为基于网络性能视频监控后端系统架构是使用传感器Web启用框架和基于云的数据存储来开发的。通过摄像机/边缘设备,文件和元数据共享以及快速云基础存储器上的模拟器获得数据。本研究旨在比较大规模视频监控的性能负载,其中小型视频监控,从基于云MCS的基于云的存储系统显示出令人满意的性能,可扩展性和良好的可靠性。最重要的功能是存储的动态调整,并且不会有任何担心空间不充分或浪费。本文提出了一种解决方案,用于部署CCTV视频监控的Web应用程序,该对象云存储服务系统基于开源云操作系统OpenStack Swift。它在IAAS上的OpenStack Swift工作,并通过多个摄像头监控(MCS)分配用于存储原始数据的资源。

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