Firefly Optimization-Based Buffer Replacement Algorithm to Improve Nand Flash Memory Performance

Abstract

Because of its shock tolerance, nonvolatility, low power consumption, and fast I/O speed, flash memory is often used for storage in consumer applications and, more recently, in the business computer environment. State drives SSDs to have not-in-place updates and asymmetric I/O latency, with write/erase operations being substantially slower than read operations. In this paper, we propose a buffer replacement technique FBRA that uses the firefly algorithm (FA) to precisely predict whether the pages residing in the buffer is hot or cold. The firefly optimization estimates hot fitness value of each page in the buffer in order to accurately classify them as hot or cold by characterizing precisely the temporal and spatial locality. To increase the hit ratio and SSD buffer use, the frequently used pages should stay longer in buffer compared to other pages. The proposed approach outperforms the existing SSD buffer management strategies regarding buffer hit ratio, write count, and runtime. Trace-driven simulation is done using FlashDB Simulator to support the performance of our approach surpasses various traditional buffer replacement policies.