NVMe SSDs have become mainstream storage devices thanks to their compact size and ultra-low latency. It has been observed that the impact of interference among all concurrently running streams (i.e., I/O workloads) on their overall responsiveness differs significantly, thus leading to unfairness. The intensity and access locality of streams are the primary factors contributing to interference. A small-sized data cache is commonly equipped in the front-end of SSDs to improve I/O performance and extend the device's lifetime. The degree of parallelism at this level, however, is limited compared to that of the SSD back end, which consists of multiple channels, chips, and planes. Therefore, the impact of interference can be more significant at the data cache level. In this paper, we propose a cache division management scheme that not only contributes to fairness but also boosts I/O responsiveness across all workloads in NVMe SSDs. Specifically, our proposal supports long-term data cache partitioning and short-term cache adjustment with global sharing, ensuring better fairness and further enhancing cache utilization efficiency in multi-stream scenarios. Trace-driven simulation experiments show that our proposal improves fairness by an average of66.0% and reduces overall I/O response time by between3.8% and18.0%, compared to existing cache management schemes for NVMe SSDs.

Zoned namespace (ZNS) SSDs are emerging storage devices offering low cost, high performance, and software definability. By adopting host-managed zone-based sequential programming, ZNS SSDs effectively eliminate the space overhead associated with on-board DRAM memory and garbage collection. However, while background read refreshing serves as a data protection mechanism in conventional block-interface SSDs, state-of-the-art ZNS SSDs lack read refreshing functionality to guarantee data reliability. Moreover, implementing zonelevel read refreshing in ZNS SSDs incurs significant overhead due to the large volume of valid data movements in a zone, leading to degraded I/O performance. To efficiently enable read refreshing for ZNS SSDs, this paper proposes FineRR-ZNS, a fine-granularity read refreshing mechanism for ZNS SSDs. FineRR-ZNS employs a host-controlled fine-granularity read refreshing scheme that selectively determines block-level read refreshing via metadata remapping. A zone reconstruction method is also designed to retrieve remapped data forming complete data during zone-level RR. Specifically, the remapped data after zone reconstruction are still available and prioritized for read access until their respective blocks need the next RR. Evaluation results show that FineRR-ZNS significantly enhances read refreshing efficiency and I/O throughput compared to zone-level read refreshing implemented in the state-of-the-art ZenFS file system.

Considering 3D NAND flash has a new property of process variation (PV) , which causes different raw bit error rates (RBER) among different layers of the flash block. This article builds a mathematical model for estimating the retention errors of flash cells, by considering the factor of layer-to-layer PV in 3D NAND flash memory, as well as the factors of program/erase (P/E) cycle and retention time of data. Then, it proposes classifying the layers of flash block in 3D NAND flash memory into profitable and unprofitable categories, according to the error correction overhead. After understanding the retention error variation of different layers in 3D NAND flash, we design a mechanism of data placement, which maps the write data onto a suitable layer of flash block, according to the data hotness and the error correction overhead of layers, to boost read performance of 3D NAND flash. The experimental results demonstrate that our proposed retention error estimation model can yield a R 2 value of 0.966 on average, verifying the accuracy of the model. Based on the estimated retention error rates of layers, the proposed data placement mechanism can noticeably reduce the read latency by 29.8 % on average, compared with state-of-the-art methods against retention errors for 3D NAND flash memory.

Sanitization is an effective approach for ensuring data security through scrubbing invalid but sensitive data pages, with the cost of impacts on storage performance due to moving out valid pages from the sanitization-required wordline, which is a logical read/write unit and consists of multiple pages in high-density SSDs. To minimize the impacts on I/O latency and data security, this article proposes a polling-based scheduling approach for data sanitization in high-density SSDs. Our method polls a specific SSD channel for completing data sanitization at the block granularity, meanwhile other channels can still service I/O requests. Furthermore, our method assigns a low priority to the blocks that are more likely to have future adjacent page invalidations inside sanitization-required wordlines, while selecting the sanitization block, to minimize the negative impacts of moving valid pages. Through a series of emulation experiments on several disk traces of real-world applications, we show that our proposal can decrease the negative effects of data sanitization in terms of the risk-performance index, which is a united time metric of I/O responsiveness and the unsafe time interval, by 16.34% , on average, compared to related sanitization methods.

Channel-level RAID implementation SSDs can fight against channel failures inside SSDs, but greatly suffer from imbalanced wear-out (i.e. erase) and I/O workloads across all SSD channels, due to the nature of in-channel updates on data/parity chunks of data stripes. This paper proposes exchanging channel locations of data/parity chunks belonging to the same stripe when satisfying update (write) requests, termed as out-of-channel data placement. Consequently, it can smooth wear-out and I/O workloads across SSD channels, thus reducing I/O response time. Through a series of emulation experiments on several realistic disk traces, we show that our proposal can greatly improve I/O performance, as well as noticeably balance the wear-out and I/O workloads, in contrast to related methods.

In flash-based solid-state drives (SSDs), certain small unaligned I/O requests span two logical pages though their size is not larger than the basic write/read unit of SSDs (i.e. an SSD page), and we term them as across-page requests. Servicing such across-page requests triggers two separated I/O operations on different SSD pages, and thus impacts the I/O performance and the endurance of SSDs. For mitigating negative effects caused by across-page requests, this paper proposes a novel flash translation layer (FTL) scheme for SSDs to separately re-align such requests via remapping them onto a single SSD page. Consequently, both read and write requests on the across-page data can be completed with one page-level I/O operation. Through a series of experiments based on the selected disk traces of real-world applications, we demonstrate that the proposed realigning method at FTL of SSD devices, can noticeably reduce the I/O latency by between 4.6% and 11.6%, and the erase number (i.e. the indicator of SSD endurance) by between 6.4% and 19.11%, compared to state-of-the-art methods.