Efficient on-line identification of hot data for flash-memory management

Abstract

Hot-data identification for flash-memory storage systems not only imposes great impacts on flash-memory garbage collection but also strongly affects the performance of flashmemory access and its life time (due to wear-levelling). In this research, we propose a highly efficient method for online hot-data identification with limited space requirements. Different from the past work, multiple independent hash functions are adopted to reduce the chance of false identification of hot data and provide predictable and excellent performance for hot-data identification. We not only propose an efficient implementation of the proposed framework but also conduct a series of experiments to verify the performance of the proposed method, in which very encouraging results are presented.