%A Wen ZHOU,Dan FENG,Yu HUA,Jingning LIU,Fangting HUANG,Yu CHEN,Shuangwu ZHANG %T Prober: exploiting sequential characteristics in buffer for improving SSDs write performance %0 Journal Article %D 2016 %J Front. Comput. Sci. %J Frontiers of Computer Science %@ 2095-2228 %R 10.1007/s11704-016-5286-z %P 951-964 %V 10 %N 5 %U {https://journal.hep.com.cn/fcs/EN/10.1007/s11704-016-5286-z %8 2016-09-07 %X

Solid state disks (SSDs) are becoming one of the mainstream storage devices due to their salient features, such as high read performance and low power consumption. In order to obtain high write performance and extend flash lifespan, SSDs leverage an internal DRAM to buffer frequently rewritten data to reduce the number of program operations upon the flash. However, existing buffer management algorithms demonstrate their blank in leveraging data access features to predict data attributes. In various real-world workloads, most of large sequential write requests are rarely rewritten in near future. Once these write requests occur, many hot data will be evicted from DRAM into flash memory, thus jeopardizing the overall system performance. In order to address this problem, we propose a novel large write data identification scheme, called Prober. This scheme probes large sequential write sequences among the write streams at early stage to prevent them from residing in the buffer. In the meantime, to further release space and reduce waiting time for handling the incoming requests, we temporarily buffer the large data into DRAM when the buffer has free space, and leverage an actively write-back scheme for large sequential write data when the flash array turns into idle state. Experimental results demonstrate that our schemes improve hit ratio of write requests by up to 10%, decrease the average response time by up to 42% and reduce the number of erase operations by up to 11%, compared with the state-of-the-art buffer replacement algorithms.