Date Added: Oct 2010
Hot data identification can be applied to a variety of fields. Particularly in flash memory, it has a critical impact on its performance (due to garbage collection) as well as its lifespan (due to wear leveling). Although this is an issue of paramount importance in flash memory, it is the least investigated one. Moreover, all existing schemes focus only or mainly on a frequency viewpoint. However, recency factor also must be considered as much importantly as the frequency for hot data identification. In this paper, the authors propose a novel hot data identification scheme adopting multiple bloom filters to efficiently capture finer-grained recency as well as frequency.