Zoned namespace solid state drives (ZNS SSDs) provide superior capacity and life span compared to conventional namespace (CNS) SSDs at the same cost. Especially, a small-zone ZNS SSD can achieve a low write amplification factor (WAF) and performance isolation among I/O streams by providing the host with finer-grained control of the SSD's flash chips than the large-zone counterpart. To maximize these advantages, multiple zones in a small-zone SSD should be grouped and operated simultaneously. A ZNS-aware file system encapsulates the ZNS interface and transforms a ZNS SSD into a general-purpose storage to the host layer. However, the current ZNS-aware file systems were designed for the large-zone ZNS SSDs, and thus lack the zone group management feature. This paper proposes a dynamic zone group management scheme for ZNS-aware file systems that dynamically adjusts the number of zone groups in accordance with the workload characteristics and the size of each zone group to achieve high performance at a low WAF. The proposed scheme was implemented in the F2FS. Our evaluation with FIO, Filebench and db_bench showed that, across all cases, the proposed scheme improved the performance by up to 71.2% while reducing the WAF by 29.8% in comparison to the static zone grouping scheme.

Storage deduplication improves write latency, increases available space, and reduces the wear of storage media by eliminating redundant writes. The flash translation layer (FTL) of a flash solid state disk (SSD) easily enables deduplication in an SSD through the simple mapping of duplicated logical pages to the same physical page. Therefore, a few deduplicating FTLs have been proposed. However, the deduplication of partially duplicated files breaks the sequentiality of data storage at the flash page level, resulting in a significant degradation of the read performance. Although increasing available storage space, reducing flash write, and extending lifespan are barely perceptible to users, extended read latency is critical to user-perceived performance. In this paper, we propose a novel deduplication FTL called Dedup-for-Speed (DFS). The DFS FTL trades surplus capacity gained through inline deduplication for improved read performance by storing duplicated pages in fast flash modes, such as the pseudo-single-level-cell(pSLC) mode. The flash mode of a page is determined by its degree of deduplications. Duplicate pages are migrated to fast flash blocks during idle intervals to minimize interference with host-issued operations. Contrary to conventional deduplication schemes, DFS improves the read performance while maintaining the aforementioned benefits of deduplication. Our evaluation of six real-world traces showed that DFS improved the read latency by 16% on average and up to 34%. It also enhanced the write latency by 64% on average and up to 82%.

The distributed shared memory (DSM)-based computation offloading scheme allows collaborative multiple threads to dynamically migrate and execute across a mobile device and computing nodes. Despite this strong advantage, it misses a significant portion of the potential performance gain because the traditional DSM model is suboptimal for computation offloading. This paper proposes an enhanced DSM model that aims to enable multiple computing nodes to efficiently and reliably offload concurrent multiple threads from a mobile device. To achieve this design goal, we propose the following novel schemes: a) selective object tracking minimizes the set of objects to be monitored by the DSM layer; b) lock-thread repartitioning dynamically relocates threads and locks in order to reduce remote lock acquisitions and inter-node synchronizations; and c) thread-state checkpointing protects the data and context upon unexpected system failures. We implemented METEOR, which is a prototype based on the proposed schemes, and evaluated it with diverse applications. The evaluation showed that METEOR, with four computing nodes, improved the performance by up to 109% and reduced energy consumption by up to 52% in comparison with the previous DSM-based offloading scheme.