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FlashNet: Flash/Network Stack Co-Design

During the past decade, network and storage devices have undergone rapid performance improvements, delivering ultra-low latency and several Gbps of bandwidth. Nevertheless, current network and storage stacks fail to deliver this hardware performance to the applications, often due to the loss of I/O... (more)

Performance Characterization of NVMe-over-Fabrics Storage Disaggregation

Storage disaggregation separates compute and storage to different nodes to allow for independent resource scaling and, thus, better hardware resource... (more)

Exploiting Internal Parallelism for Address Translation in Solid-State Drives

Solid-state Drives (SSDs) have changed the landscape of storage systems and present a promising storage solution for data-intensive applications due... (more)

Management of Next-Generation NAND Flash to Achieve Enterprise-Level Endurance and Latency Targets

Despite its widespread use in consumer devices and enterprise storage systems, NAND flash faces a growing number of challenges. While technology... (more)

LibPM: Simplifying Application Usage of Persistent Memory

Persistent Memory devices present properties that are uniquely different from prior technologies for which applications have been built. Unfortunately, the conventional approach to building applications fail to either efficiently utilize these new devices or provide programmers a seamless development experience. We have built LibPM, a Persistent... (more)

Towards Robust File System Checkers

File systems may become corrupted for many reasons despite various protection techniques. Therefore, most file systems come with a checker to recover the file system to a consistent state. However, existing checkers are commonly assumed to be able to complete the repair without interruption, which... (more)

HIL: A Framework for Compositional FTL Development and Provably-Correct Crash Recovery

We present a framework called Hierarchically Interacting Logs (HIL) for constructing Flash Translation Layers (FTLs). The main goal of the HIL framework is to heal the Achilles heel —the crash recovery—of FTLs (hence, its name). Nonetheless, the framework itself is general enough to... (more)

NEWS

  • TOS EiC Professor Sam H. Noh of UNIST named as ACM Distinguished Member
    A complete list of 2017 ACM Distinguished Members can be found here.

  • CFP - Special Issue on NVM and Storage (in detail)

  • TOS Editor-in-Chief featured in "People of ACM"
    Sam H. Noh is Editor-in-Chief of ACM Transactions on Storage (TOS) - featured in the periodic series "People of ACM", full article available here
    November 01, 2016
     

  • ACM Transaction on Storage (TOS) welcomes Sam H. Noh as its new Editor-in-Chief for a 3-year term, effective August 1, 2016.
    Sam H. Noh is a professor and Head of the School of the Electrical and Computer Engineering School at UNIST (Ulsan National Institute of Science and Technology) in Ulsan, Korea and a leader in the use of new memory technology such as flash memory and non-volatile memory in storage.
    - August 01, 2016

Forthcoming Articles
Leveraging Glocality of Cube-Based Networks for Fast Failure Recovery in Distributed RAM Storage

Distributed RAM storage aggregates the RAM of servers in data center networks (DCN) to provide extremely high I/O performance for large-scale cloud systems. For quick recovery of storage server failures, MemCube exploits the proximity of the BCube network to limit the recovery traffic to the recovery servers' 1-hop neighborhood. However, previous design is applicable only to the symmetric BCube(n,k) network with n^{k+1} nodes, and has suboptimal recovery performance due to congestion and contention. To address these problems, in this paper we propose CubeX, which (i) generalizes the "1-hop" principle of MemCube for arbitrary cube-based networks, and (ii) improves the throughput and recovery performance of RAM-based key-value (KV) store via cross-layer optimizations. At the core of CubeX is to leverage the glocality (= globality + locality) of cube-based networks: it scatters backup data across a large number of disks globally distributed throughout the cube, and restricts all recovery traffic within the small local range of each server node. Our evaluation shows that CubeX not only efficiently supports RAM-based KV store for cube-based networks, but also significantly outperforms MemCube and RAMCloud in both throughput and recovery time.

TDDFS: A Tier-aware Data Deduplication-based File System

Storage-tiering becomes a way of achieving better performance and cost-effectiveness at the same time. In the tiered storage systems, storage tier with higher performance (fast-tier) is used to store the frequently accessed (active) data while a large amount of less active data is stored in the lower performance tier (slow-tier). Data is migrated between different tiers according to its activeness. In this paper, we propose a Tier-aware Data Deduplication based File System, called TDDFS, which can operate efficiently on top of a two-tier storage environment. Specifically, to achieve better performance, nearly all file operations are performed at the fast-tier. To achieve higher cost-effectiveness, files are migrated from the fast-tier to the slow-tier if they are no longer active and this migration is done with data deduplication to eliminate the redundant data in the slow-tier. The uniqueness of our design is to maintain the non-redundant (unique) chunks produced by data deduplication in both tiers if possible. To improve deduplication efficiency, TDDFS avoids re-deduplicating the reloaded file if the data chunks of the file are not modified. Our evaluation shows that TDDFS achieves high performance, high data migration efficiency, and low space utilization at the same time.

On the Lifecycle of the File

Liquid Cloud Storage

A liquid system provides durable object storage based on spreading redundantly generated data across a network of hundreds to thousands of potentially unreliable storage nodes. A liquid system uses a combination of a large code, lazy repair, and a flow storage organization. We show that a liquid system can be operated to enable flexible and essentially optimal combinations of storage durability, storage overhead, repair bandwidth usage, and access performance.

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