A Survey on the Integration of NAND Flash Storage in the Design of File Systems and the Host Storage Software Stack

With the ever-increasing amount of data generate in the world, estimated to reach over 200 Zettabytes by 2025, pressure on efficient data storage systems is intensifying. The shift from HDD to flash-based SSD provides one of the most fundamental shifts in storage technology, increasing performance capabilities significantly. However, flash storage comes with different characteristics than prior HDD storage technology. Therefore, storage software was unsuitable for leveraging the capabilities of flash storage. As a result, a plethora of storage applications have been design to better integrate with flash storage and align with flash characteristics. In this literature study we evaluate the effect the introduction of flash storage has had on the design of file systems, which providing one of the most essential mechanisms for managing persistent storage. We analyze the mechanisms for effectively managing flash storage, managing overheads of introduced design requirements, and leverage the capabilities of flash storage. Numerous methods have been adopted in file systems, however prominently revolve around similar design decisions, adhering to the flash hardware constrains, and limiting software intervention. Future design of storage software remains prominent with the constant growth in flash-based storage devices and interfaces, providing an increasing possibility to enhance flash integration in the host storage software stack

A Survey on the Integration of NAND Flash Storage in the Design of File Systems and the Host Storage Software Stack

With the ever-increasing amount of data generate in the world, estimated to reach over 200 Zettabytes by 2025, pressure on efficient data storage systems is intensifying. The shift from HDD to flash-based SSD provides one of the most fundamental shifts in storage technology, increasing performance capabilities significantly. However, flash storage comes with different characteristics than prior HDD storage technology. Therefore, storage software was unsuitable for leveraging the capabilities of flash storage. As a result, a plethora of storage applications have been design to better integrate with flash storage and align with flash characteristics. In this literature study we evaluate the effect the introduction of flash storage has had on the design of file systems, which providing one of the most essential mechanisms for managing persistent storage. We analyze the mechanisms for effectively managing flash storage, managing overheads of introduced design requirements, and leverage the capabilities of flash storage. Numerous methods have been adopted in file systems, however prominently revolve around similar design decisions, adhering to the flash hardware constrains, and limiting software intervention. Future design of storage software remains prominent with the constant growth in flash-based storage devices and interfaces, providing an increasing possibility to enhance flash integration in the host storage software stack

Understanding and Improving the Performance of Read Operations Across the Storage Stack

We live in a data-driven era, large amounts of data are generated and collected every day. Storage systems are the backbone of this era, as they store and retrieve data. To cope with increasing data demands (e.g., diversity, scalability), storage systems are experiencing changes across the stack. As other computer systems, storage systems rely on layering and modularity, to allow rapid development. Unfortunately, this can hinder performance clarity and introduce degradations (e.g., tail latency), due to unexpected interactions between components of the stack. In this thesis, we first perform a study to understand the behavior across different layers of the storage stack. We focus on sequential read workloads, a common I/O pattern in distributed le systems (e.g., HDFS, GFS). We analyze the interaction between read workloads, local le systems (i.e., ext4), and storage media (i.e., SSDs). We perform the same experiment over different periods of time (e.g., le lifetime). We uncover 3 slowdowns, all of which occur in the lower layers. When combined, these slowdowns can degrade throughput by 30%. We find that increased parallelism on the local le system mitigates these slowdowns, showing the need for adaptability in storage stacks. Given the fact that performance instabilities can occur at any layer of the stack, it is important that upper-layer systems are able to react. We propose smart hedging, a novel technique to manage high-percentile (tail) latency variations in read operations. Smart hedging considers production challenges, such as massive scalability, heterogeneity, and ease of deployment and maintainability. Our technique establishes a dynamic threshold by tracking latencies on the client-side. If a read operation exceeds the threshold, a new hedged request is issued, in an exponential back-off manner. We implement our technique in HDFS and evaluate it on 70k servers in 3 datacenters. Our technique reduces average tail latency, without generating excessive system load

Designing the replication layer of a general-purpose datacenter key-value store

Online services and cloud applications such as graph applications, messaging systems, coordination services, HPC applications, social networks and deep learning rely on key-value stores (KVSes), in order to reliably store and quickly retrieve data. KVSes are NoSQL Databases with a read/write/read-modify-write API. KVSes replicate their dataset in a few servers, such that the KVS can continue operating in the presence of faults (availability). To allow programmers to reason about replication, KVSes specify a set of rules (consistency), which are enforced through the use of replication protocols. These rules must be intuitive to facilitate programmer productivity (programmability). A general-purpose KVS must maximize the number of operations executed per unit of time within a predetermined latency (performance) without compromising on consistency, availability or programmability. However, all three of these guarantees are at odds with performance. In this thesis, we explore the design of the replication layer of a general-purpose KVS, which is responsible for navigating this trade-off, by specifying and enforcing the consistency and availability guarantees of the KVS. We start the exploration by observing that modern, server-grade hardware with manycore servers and RDMA-capable networks, challenges conventional wisdom in protocol design. In order to investigate the impact of these advances on protocols and their design, we first create an informal taxonomy of strongly-consistent replication protocols. We focus on strong consistency semantics because they are necessary for a general-purpose KVS and they are at odds with performance. Based on this taxonomy we carefully select 10 protocols for analysis. Secondly, we present Odyssey, a frame-work tailored towards protocol implementation for multi-threaded, RDMA-enabled, in-memory, replicated KVSes. Using Odyssey, we characterize the design space of strongly-consistent replication protocols, by building, evaluating and comparing the 10 protocols. Our evaluation demonstrates that some of the protocols that were efficient in yesterday’s hardware are not so today because they cannot take advantage of the abundant parallelism and fast networking present in modern hardware. Conversely, some protocols that were inefficient in yesterday’s hardware are very attractive today. We distil our findings in a concise set of general guidelines and recommendations for protocol selection and design in the era of modern hardware. The second step of our exploration focuses on the tension between consistency and performance. The problem is that expensive strongly-consistent primitives are necessary to achieve synchronization, but in typical applications only a small fraction of accesses is actually used for synchronization. To navigate this trade-off, we advocate the adoption of Release Consistency (RC) for KVSes. We argue that RC’s one-sided barriers are ideal for capturing the ordering relationship between synchronization and non-synchronization accesses while enabling high performance. We present Kite, a general-purpose, replicated KVS that enforces RC through a novel fast/slow path mechanism that leverages the absence of failures in the typical case to maximize performance, while relying on the slow path for progress. In ad dition, Kite leverages our study of replication protocols to select the most suitable protocols for its primitives and is implemented over Odyssey to make the most out of modern hardware. Finally, Kite does not compromise on consistency, availability or programmability, as it provides sufficient primitives to implement any algorithm (consistency), does not interrupt its operation on a failure (availability), and offers the RC API that programmers are already familiar with (programmability)