Model based predictive prefetching

Web caching and web prefetching are two effective techniques to latency reduction. However, most previous research has addressed only one of these two techniques separately. In this work, we propose an integrated web-caching and web-prefetching model, where the issues of prefetching aggressiveness, replacement policy and increased network traffic are addressed together in an integrated framework. The core of our integrated solution is a prediction model based on statistical correlation between web objects. The model is trained on realistic web server logs. By utilizing the predictive power of the model, we develop an integrated prefetching and caching algorithm, Pre-GDSF. We conduct simulations to examine the effectiveness of our algorithm. We show the tradeoff between latency reduction and increased network traffic achieved by Pre-GDSF. We also show why prefetching is more effective for smaller caches than for larger ones.

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