云环境下基于多虚拟机的在线视频监控系统设计

Online Video Surveillance System Designed Under Cloud of Virtual Machines Based on Multi

摘要:

针对常规视频监控系统在线实时性不强,海量视频数据传输迟滞,任务管理单一等问题,提出了构建在云计算环下基于多虚拟机技术在线视频监控系统；利用云计算平台中的物理资源与服务资源提升在线视频监控系统数据处理能力,虚拟机可同时处理大量的视频监控数据,并将视频数据以云存储的方式存储于云端服务器,降低了设备建设成本,可根据不同用户需求定制相关服务；本系统基于云计算平台设计,应用数十台乃至数百台虚拟机对在线视频监控数据进行处理,设计实现了云平台下在线视频监控系统的结构设计、以太网通信接口设计、服务器硬件配置和虚拟机控制；在软件设计方面通过对各虚拟机资源利用率的计算而动态分配资源,从而可以有效减少网络传输系统状态信息的带宽开销；通过系统功能与性能测试表明,在常规公共网络10 M带宽的情况下,本系统在线视频监控数据的传输延迟时间相比于传统视频监控减少了85%以上,监控视频数据量减少了75%以上。

Abstract:

Conventional video monitoring systems for real-time online is not strong, massive video data transmission delay, single issues such as task management, proposed to build in the cloud computing ring virtual machine technology based on multi-line video surveillance systems, the use of cloud computing platforms and physical resources service resources to enhance the online video surveillance system data processing capabilities, a virtual machine can handle large amounts of video surveillance data, and video data stored in the cloud storage cloud server, reducing the construction cost of equipment, related services can be customized according to the needs of different users . The system is cloud computing platform design, application dozens or even hundreds of virtual machines based on monitoring data for online video processing, design and implementation of the structural design of the cloud platform for online video surveillance system, Ethernet communication interface design, server hardware configuration and virtual Machine Control. By calculating each virtual machine resource utilization and dynamic allocation of resources in software design, which can effectively reduce the cost of network bandwidth transmission system status information. The system function and performance testing shows that in the case of a conventional public network bandwidth is 10M, the transmission line of the video surveillance system, the delay time of the data compared to traditional video surveillance reduced more than 85%, more than 75% reduction in monitoring the amount of video data.