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Web prefetching is a promising solution used to reduce user's latency and improve the QOS.This paper presents a popularity-based selective Markov prefetching model for predicting the forthcoming Web pages.We make use of teh Zipf's law to model the Web objects' popularity.An experimental evaluation of the prefetching mechanism is presented using real server(More)
—The key of prefetching techniques is to establish an effective prediction model, which is mainly classified into two main categories according to the data structure namely PPM model and DG model. However, both models have their own shortcoming. To overcome their shortcomings, we will propose an improved algorithm based on exponential descendent double(More)
Current prefetching models mainly depend on prediction algorithms to fetch Web objects in advance, but lack the consideration of the prefetchability of Web objects. If the prefetchability of the objects can be considered before prefetching, unnecessary prefetching will be decreased to some extent. On one hand, it can improve hit ratio of prefetching(More)
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