Today Internet has become an integral part of most of our life. The attempt to display media files through Internet was started from the mid-20th century. Video distribution is pointed out as one of the most promising applications of the Internet. Nevertheless, this application is a costly service to provide because of its quality-of-service requirements and the number of potential users. In order to guarantee scalability, providers often serve low-quality videos with no continuous reception. Thus, most of the users are not satisfied with the quality of received video. The proposed research work aims to implement the Video on Demand Service in Cloud Environment in a more secure, scalable and cost effective manner. This paper addresses the problem of optimizing the playback delay experienced by a population of heterogeneous clients, in video streaming applications. We consider a scenario, where clients subscribe to different portions of a scalable video stream, depending on their capabilities. This paper examines the challenges that make simultaneous delivery and playback, or streaming, of video difficult, and explores algorithms and systems that enable streaming of on demand video over packet networks such as the Internet. Prediction Based Resource Algorithm is proposed that the video content is distributed in the form of frames and considering random frames to be sequentially loaded into the user memory .To provide security to the provided content ,the uploaded file is manually audited. This minimizes the buffering delay of the video content irrespective of the bandwidth and provides appropriate content to the clients.