Research And Design Of Medical Video On Demand System Based On HDFS Cluster

With the advent of the "Internet Plus" era,information technology has developed rapidly.The medical video on demand system has become a fast information dissemination medium and has been widely used in the medical field.In order to construct a medical video on demand system with perfect on-demand function and strong storage capacity,this paper combines video on demand technology with cloud storage technology,and designs a medical video on demand system based on HDFS cluster.The system can effectively improve the video storage capacity of the system and improve the service quality of the medical video on demand system on the basis of realizing the medical video on demand function.The main research content of this article includes the following parts:Firstly,the thesis begins with the system requirements analysis and the overall architecture,completes the design and construction of the server-side based on HDFS cluster,and makes full preparation for the realization of the system.The network structure model of the system adopts B/S mode with strong distribution and convenient business expansion,the system design uses Java Web technology and streaming media technology,using a front-end development language such as HTML5,DIV+CSS,and JavaScript to present a user-friendly and intuitive interface,VLC streaming media player is used to embed web pages to realize medical video on demand.Through the functional test of the system,the system meets the expected design goals,and can achieve user registration,user login,video query,video on demand,user management and video data management functions.At the same time,the HDFS cluster storage mode used in this paper is compared with the access performance of files under traditional FTP,so as to verify the high efficiency of the video storage scheme adopted in this paper.Secondly,through analysis,it is found that HDFS’s default random data placement strategy can easily lead to unbalanced storage during data writing,therefore,the HDFS default data placement strategy is optimized,for the current running status of the DataNodes,select the DataNode with the best comprehensive conditions for data storage.Finally,through simulation experiments,it is further illustrated that the algorithm used in this paper is able to use the system’s storage space reasonably and efficiently compared with the HDFS’s own algorithm,improve the video storage load balancing capability of the system,and improve the service quality of the medical video on demand system.