Researches On Cache Algorithm Based On Exponential Segmentation For Streaming Media Proxy Cache

As the development of the Internet and multimedia technology, the application of streaming media is becoming more and more popular. However, the current Internet lacks support for real-time communication, which influencing the performance of media transmission. Furthermore, due to the high demands of streaming media transmission on system I/O and network bandwidth, the server and network bandwidth turn into the bottleneck of the whole system. While such problems can be effectively solved by the proxy caching technology, which caches part or all of the data of hot programs so as to offer services to the users nearby. Therefore, based on the main features of the application of streaming media, studies on efficient proxy caching strategy to increase caching hit rate, decrease the client startup latency and reduce server overloads and network resource consumption are of great significance to the research of proxy caching technology of streaming media.Based on the main factors influencing the streaming media caching performance and transmission resource consumption, this paper discusses the proxy strategy . Cache replacement algorithms directly affect the efficiency of the proxy cache system, and the main research on cache replacement algorithms is how to replace cache object so that users can access media object directly from the cache. Existing cache replacement algorithms have the problem of inaccurate evaluation of the caching utility because their standards are access times and frequency of the media, additionly they don't consider the probability of access objects in the future, and the evaluation of cache utility is not accurate, and the calculation of cache utility is constrained to the whole media object but not accurately to the segment. To solve these prolems, the paper presents the cache replacement algorithm based on LRV. This algorithm builds the base on exponential segmentation, refines the scheduling granularity of cache space, and the calculation of cache utility is based on segments, the media partial validity, the probability of access to segment in the future, segment access frequency, segment average access length and the influence of cached segment size to cache utility are all considered in this algorithm, which enhances the cache performance.The results of simulation experiments show that the streaming media proxy cache algorithm presented in this paper has better performance on increasing cache hit rate and reducing client startup latency rate,Therefore, the streaming media proxy cache algorithm presented in this paper helps to improve the transmission efficiency and media quality perceived by the end user.