A prefetching scheme based on the analysis of user access patterns in news-on-demand system

Abstract

The NOD article makes a difference to VOD data in terms of media type, size, creation interval and user interactivity. Because of these intrinsic characteristics, user access patterns of the NOD article can be different from that of VOD data. In this paper, we analyze the log file of one electronic newspaper to show the short-term popularity and long-term popularity patterns. Based on these patterns, we propose LLBF (Largest Life-cycle Based Frequency) prefetching scheme that uses the two popularity patterns to cache a set of popular articles. In Simulation, we show that the proposed LLBF prefetching scheme increases hit ratio, and reduces the number of replacements more than other replacement algorithms as a small number of articles such as headline news is prefetched in main memory.