Efficient identification of hot data for flash memory storage systems

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 flash memory access and its lifetime (due to wear-levelling). This research proposes a highly efficient method for on-line hot data identification with limited space requirements. Different from past work, multiple independent hash functions are adopted to reduce the chance of false identification of hot data and to provide predictable and excellent performance for hot data identification. This research not only offers an efficient implementation for the proposed framework, but also presents an analytic study on the chance of false hot data identification. A series of experiments was conducted to verify the performance of the proposed method, and very encouraging results are presented.