Based On Web Objects Popularity Of Pre-fetching Model

Presently caching and prefetching techniques are the primary solutions used to reduce Web access latency. Web caching technique has been widely used in different places of Internet.But as dynamic documents and personal services increase all over the world, the performance of caching deteriorates significantly. As a result, Web prefetching which is a efficient way of making up for Web caching, and the most effective method to break theupper bound of caching performance--is becoming a hotspot in Web speedup researcharea.There are two problems to be solved before prefecting can be put into practice: One isprediction--deciding which are the most likely Web objects before the users take the action.,the other is determining which Web objects will be prefetched and how many Web objects can be prefetched on the basis of the current state of system. Aiming at these two problems, we propose a PPM prefetching model based on Web objects' popularity in which existing prediction algorithms and prefetching control strategies are improved.Therefore, a high prediction precision can be achieved at the cost of relative low storage complexity and network traffic.First, this thesis introduces the development and the state of the art of the Internet and WWW, gives the problems Internet faces and corresponding solutions; and describes the concept, classification and structure of Web caching and prefetching; then summarizes existing cache replacement algorithms, follows the existing prediction algorithms and prefetching control strategies.After a brief comment on existing prediction algorithms and prefetching control strategies,we propose a prefetching model,the core of which is a PPM predicting model based on Web objects' popularity deciding which Web objects are good for being prefetched. Not only this new prediction model is easy to be implemented, but also can achieve a high prediction precision at the cost of relative low storage complexity and network traffic. Moreover,we discuss the prefecting control problems, in which a more practical formula figuring out prefetching threshold dynamically is given.This formula solves which Web objects are prefetched and how many Web objects are prefetched on the basis of prediction information provided by prediction model.Finally, experiments have been made based on the prediction model and experimentalresults are analyzed.