Caching Policy With User Behavior Characteristics In P2P Streaming Media On-demand System

With the improvement of convection media users demand, the increase in the number of users, the traditional C/S architecture model is easy to cause performance bottlenecks, affect the further development of streaming media technology and widely used. Traditional caching policy does not take into consideration of the user’s behavior, in order to better support streaming media on demand system, based on the study of caching strategies from the aspects of user behavior characteristics more to think about how to design the caching policy, so in the new cache management strategy, this article will demand behavior characteristics of the user into caching policy, has resulted in a data cache on-demand streaming media system more reasonable, specific research summary is as follows:This paper introduces the concept of P2P and the basic concept of streaming media, and introduces the several factors affecting the smooth video playback. Due to the unreasonable of cache management strategy, the first start playback delay caused by the phenomenon such as network jitter. In order to reduce the waiting time when users to watch video programs, let the user node in the system more stable lies in the system, the need to design can be efficiently used to cache space caching strategies.Due to stored in the cache space and replace data blocks is not reasonable, the user for frequent operation will be more influence cache space change into change frequently, this is because there is no effective management cache space. Because the streaming media on demand system of user interaction ability is greatly increased, the traditional caching algorithm does not take into consideration of the a factor, so this article caching strategies in the design, on the basis of caching strategies before, mainly considering the characteristics of the user operation behavior.Users can in streaming media on demand system for VCR (fast forward, fast rewind and suspension, etc.), and the user may at any time to join or exit system, these are the key aspects of user behavior characteristics. On the basis of the deep analysis of these factors, this paper puts forward a data block popularity and the concept of the value of supply and demand, based on the data block in the popularity and the value of supply and demand and puts forward the corresponding cache replacement strategy.Due to the realistic environment is more complex, in order to validate the presented based on user behavior feature of caching policy is reasonable, this paper USES the current relatively popular in the simulation software for validation, the experimental conclusion is based on user behavior feature of caching strategies as a whole is better than traditional strategy.