Hot and Cold Data Identification for Flash Memory Using Multiple Bloom Filters

Abstract—In flash memory, hot data identification has a critical impact on its performance (due to a garbage collection) as well as its lifespan (due to a wear leveling). Although it is an issue of paramount importance in flash memory, little investigation has been made. Moreover, all existing schemes focus almost exclusively on a frequency viewpoint. However, recency also must be considered equally with the frequency for effective hot data identification. In this paper, we propose a novel hot data identification scheme adopting multiple bloom filters to efficiently capture finer-grained recency as well as frequency. In addition to this scheme, we propose a Window-based Direct Address Counting (WDAC) algorithm to approximate an ideal hot data identification as our baseline by using a sliding window concept. Our experimental evaluation demonstrates that our scheme not only consumes 50% less memory and requires less computational overhead up to 58%, but also improves its performance up to 65%.