Probabilistic Page Replacement Policy in Buffer Cache Management for Flash-Based Cloud Databases

Abstract

In the fast evolution of storage systems, the newly emerged flash memory-based Solid State Drives (SSDs) are becoming an important part of the computer storage hierarchy. Amongst the several advantages of flash-based SSDs, high read performance, and low power consumption are of primary importance. Amongst its few disadvantages, its asymmetric I/O latencies for read, write and erase operations are the most crucial for overall performance. In this paper, we proposed two novel probabilistic adaptive algorithms that compute the future probability of reference based on recency, frequency, and periodicity of past page references. The page replacement is performed by considering the probability of reference of cached pages as well as asymmetric read-write-erase properties of flash devices. The experimental results show that our proposed method is successful in minimizing the performance overheads of flash-based systems as well as in maintaining the good hit ratio. The results also justify the utility of a genetic algorithm in maximizing the overall performance gains.

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

“…To minimize the cost of writing dirty pages back to NAND flash memory, various algorithms have focused on reasonably increasing the read count to decrease the write count while avoiding a severe drop in the hit ratio [12][13][14][15]. LRU (Least Recently Used)-based algorithms focus on the last access time of the data page, while LFU (Least Frequently Used)-based algorithms emphasize the access frequency.…”