There has been an increasing trend in designing the Video-on-Demand systems using parallel server-based architectures to meet the client demands for online streaming of videos.We use a distributed architecture for effective Buffer management which efficiently utilizes various server resources like the disk Bandwidth, memory utilization and provides clients with VCR like functionalities.
To choose the best caching technique for VOD, one should note that traditional caching algorithms, such as LRU, do not work well for video servers due to the large size of video objects and result in low cache hit ratio. One alternative to traditional caching algorithms is interval caching policy. We have proposed a new Cooperative Interval Caching Algorithm which implements caching in distributed systems and allows distributed caches in the cluster to cooperate together to produce a high cache performance close to that of one large cache with the same size as their integral size, while minimizing the probing overhead by intelligently directing a request to the most appropriate server which has the cached stream.
We also propose a unique On-line dynamic buffer replacement policy that does not base its results solely on a single parameter such as video popularity but calculates a cumulative popularity based on several other factors and hence chooses the video with the least popularity thus calculated.
It is necessary to batch requests to minimize the bandwidth requirement, to reduce I/O demand, improve throughput and increase the number of customers served by using less number of streams. We propose a Modified Adaptive Batching Policy for batching requests arriving at a server. This is different from the existing adaptive batching techniques which batch a user request into a multicast stream by increasing the speed of transmission in the unicast stream and hence batching it. Here, instead we compare the user arrival with a threshold batch time and according to the difference we assign users to different streams classified as multicast queue, submulticast queue and unicast queue.
We also propose to implement distributed streaming of videos to clients using the Real Time Streaming protocol (RTSP) which being a control protocol is designed to add more VCR like functionalities to the streaming process. To enable the implementation of the RTSP protocol, we intend to develop a customized portal which supports the RTSP protocol.