Patch Algorithm-based Streaming Media Proxy Cache Methods

Due to the high bandwidth requirements and the long-live nature of video, server and network bandwidths are proved to be major limiting resource in the widespread usage of steaming media over the internet. The conflicts between limited internet's resources and wide application of streaming media are more serious, So it becomes a popular question in the streaming media area that how to improve the delivery quality.This paper introduces the streaming media proxy caching and the patching algorithm firstly, then we propose an efficient method of streaming media proxy caching based on patching algorithm. Lastly, we design and implement this method.The proxy cache can decrease the network bandwidth, depress the network flux, reduce the network delay and alleviate the pressure of the server. At the same time, it can promise the quality of server.Batching scheduling technology divides the time that the proxy serve to client into lots of interval. In order to use the multicast priority and save the network bandwidth, the proxy will give multicast delivery to the clients who reach the proxy at the interval and will have only one regular channel at each internal. But the batching scheduling has the defect that it will have sometime start-up delay for some clients because it have lots of clients sharing a multicast streaming. So someone proposes the patching algorithm based on the batching scheduling. The client will join in the regular channel if he misses some media data, then he can get the data from the patching channel. The method will remove the start-up delay.So we apply the patching method in the streaming media server to streaming media proxy caching, and propose an efficient method of streaming media proxy caching based on patching algorithm. Our method is as fellows: we can give a regular streaming start-up period, the proxy server can get streaming media data from the original server by unicast in this period, the time of the proxy serving to the client can divide into lots of interval, the client can join into the regular channel at the batching interval, when the proxy transmit the data for the one interval clients, it will also cache the dada for the latter client. When the latter client misses some data, the proxy can compensate the missing data using the caching data. In a regular streaming period, we can only start-up one regular channel, we can meet lots of batching clients. The method combines the proxy caching with patching algorithm, and we needn't start the patching channel between the original server and the proxy server. From the analysis, we can find the method can reduce significantly the consumption of aggregate bandwidth on backbone network bandwidth.We believe that the method proposed in this paper has some reference merit.