An Adaptive Buffer Cache Management Scheme

Chang, Hsung-Pin; Chiang, Chien-Hsieh; Yu, Yu-Cheng

doi:10.1109/ics.2016.0033

Cited by 2 publications

(1 citation statement)

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“…LRU-based algorithms lack the consideration of other history access information in addition to recency, and they simply regard that the pages with large R values are impossible to be used soon. LIRS effectively uses multiple sources of history access information, responsively changes the status of all the referenced pages, and improves the I/O performance of the storage device [24]. In the LIRS algorithm, all the accessed pages are classified into two sets: the high IRR (HIR) set and the low IRR (LIR) set.…”

Section: Introductionmentioning

confidence: 99%

PA-LIRS: An Adaptive Page Replacement Algorithm for NAND Flash Memory

et al. 2020

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NAND flash memory is increasingly widely used as a storage medium due to its compact size, high reliability, low-power consumption, and high I/O speed. It is important to select a powerful and intelligent page replacement algorithm for NAND flash-based storage systems. However, the features of NAND flash, such as the asymmetric I/O costs and limited erasure lifetime, are not fully taken into account by traditional strategies. In order to address these existing shortcomings, this paper suggests a new page replacement algorithm, called probability-based adjustable algorithm onlow inter-reference recency set (PA-LIRS). PA-LIRS completely exploits the “recency” and “frequency” information simultaneously to make a replacement decision. PA-LIRS gives a greater probability to clean pages and a smaller probability to dirty pages when evict selection happens. In addition, this proposed algorithm dynamically adjusts the parameter based on the workload pattern to further improve the I/O performance of NAND flash memory. Through a series of comparative experiments on various types of synthetic traces, the results show that PA-LIRS outperforms the previous studies in most cases.

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Section: Introductionmentioning

confidence: 99%