Research And Implementation Of Video Streaming Transportation And Preservation In Datacenter

Applications based on cloud computing platform can handle huge amounts of data, and provide users with more reliable and more efficient service, which has been rapid development. The focus is how to combine the video surveillance and cloud computing platform in order to reliably save vast amounts of video data, video retrieval and playback services for mass users.This thesis analyzes the traditional architecture of distributed data centers. Through the design of optimized video streaming and storage, we put forward a unified architecture of distributed data center-based cloud computing platform. For the part of video streaming transportation, we study and design of the flow balancer and acquisition modules, buffers, and thread pool. These modules can improve the overall quality of service. In the storage portion of the video stream, we study and design the strategy based on load balancing and document replacement mechanism. These designs make the system provide more reliable service in the case of limited resources.The system of data center was tested in a lab environment and test results show that the system can save the data reliably and efficiently provide users with on-demand service for large-scale video surveillance environment in the Internet of Things.