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Many proxy servers are limited by their file I/O needs. Even when a proxy is configured with sufficient I/O hardware, the file system software often fails to provide the available bandwidth to the proxy processes. Although specialized file systems may offer a significant improvement and overcome these limitations, we believe that user-level disk management on top of industry-standard file systems can offer similar performance advantages. In this paper, we study the overheads associated with file I/O in web proxies, we investigate their underlying causes, and we propose Web-Conscious Storage Management, a set of techniques that exploit the unique reference characteristics of web-page accesses in order to allow web proxies to overcome file I/O limitations. Using realistic trace-driven simulations, we show that these techniques can improve the proxy's secondary storage I/O throughput by a factor of 15 over traditional open-source proxies, enabling a single disk to serve over 400 (URL-get) operations per second. We demonstrate our approach by implementing Foxy, a web proxy which incorporates our techniques. Experimental evaluation suggests that Foxy outperforms traditional proxies, such as SQUID, by more than a factor of four in throughput, without sacrificing response latency.

Efficient data storage, a major concern in the modern computer industry, is mostly provided today by traditional magnetic disks. However, the cost of a disk transfer (measured in processor cycles) continues to increase with time, making disk accesses increasingly expensive. In this paper we describe the design, implementation and evaluation of a Network RamDisk device that uses main memory of remote workstations as a faster-than-disk storage device. In our study we propose various reliability policies, making the device tolerant to single workstation crashes. We show that the Network RamDisk is portable, flexible, and can operate under any of the existing Unix file systems. The Network RamDisk has been implemented both on the Linux and the Digital Unix operating systems, as a block device driver without any modifications to the kernel code. Using several real applications and benchmarks, we measure the performance of the Network RamDisk over an Ethernet and an ATM network, and find it to be usually four to eight times better than the magnetic disk. In one benchmark, our system was two orders of magnitude faster than the disk. We believe that a Network RamDisk can be efficiently used to provide reliable low-latency access to files that would otherwise be stored on magnetic disks.

In this work, we examine how transparent block-level compression in the I/O path can improve both the space efficiency and performance of online storage. We present ZBD , a block-layer driver that transparently compresses and decompresses data as they flow between the file-system and storage devices. Our system provides support for variable-size blocks, metadata caching, and persistence, as well as block allocation and cleanup. ZBD targets maintaining high performance, by mitigating compression and decompression overheads that can have a significant impact on performance by leveraging modern multicore CPUs through explicit work scheduling. We present two case-studies for compression. First, we examine how our approach can be used to increase the capacity of SSD-based caches, thus increasing their cost-effectiveness. Then, we examine how ZBD can improve the efficiency of online disk-based storage systems. We evaluate our approach in the Linux kernel on a commodity server with multicore CPUs, using PostMark, SPECsfs2008, TPC-C, and TPC-H. Preliminary results show that transparent online block-level compression is a viable option for improving effective storage capacity, it can improve I/O performance up to 80% by reducing I/O traffic and seek distance, and has a negative impact on performance, up to 34%, only when single-thread I/O latency is critical. In particular, for SSD-based caching, our results indicate that, in line with current technology trends, compressed caching trades off CPU utilization for performance and enhances SSD efficiency as a storage cache up to 99%.

Flash-based solid state drives (SSDs) exhibit potential for solving I/O bottlenecks by offering superior performance over hard disks for several workloads. In this work we design Azor, an SSD-based I/O cache that operates at the block-level and is transparent to existing applications, such as databases. Our design provides various choices for associativity, write policies and cache line size, while maintaining a high degree of I/O concurrency. Our main contribution is that we explore differentiation of HDD blocks according to their expected importance on system performance. We design and analyze a two-level block selection scheme that dynamically differentiates HDD blocks, and selectively places them in the limited space of the SSD cache. We implement Azor in the Linux kernel and evaluate its effectiveness experimentally using a server-type platform and large problem sizes with three I/O intensive workloads: TPC-H, SPECsfs 2008, and Hammerora. Our results show that as the cache size increases, Azor enhances I/O performance by up to 14.02×, 1.63×, and 1.55× for each workload respectively. Additionally, our two-level block selection scheme further enhances I/O performance compared to a typical SSD cache by up to 95%, 16%, and 34% for each workload, respectively.

As the number of user-managed devices continues to increase, the need for synchronizing multiple file hierarchies distributed over devices with ad hoc connectivity, is becoming a significant problem. In this paper, we propose a new approach for efficient cloud-based synchronization of an arbitrary number of distributed file system hierarchies. Our approach maintains both the advantages of peer-to-peer synchronization with the cloud-based approach that stores a master replica online. In contrast, we do not assume storage of any user's data in the cloud, so we address the related capacity, cost, security, and privacy limitations. Finally, the proposed system performs data synchronization in a peer-to-peer manner, eliminating cost and bandwidth concerns that arise in the “cloud master-replica” approach.

High-performance storage systems are evolving towards decentralized commodity clusters that can scale in capacity, processing power, and network throughput. Building such systems requires: (a) Sharing physical resources among applications; (b) Sharing data among applications; (c) Allowing customized data views. Current solutions typically satisfy the first two requirements through a cluster file-system, resulting in monolithic, hard-to-manage systems. In this paper we present a storage system that addresses all three requirements by extending the block layer below the file-system. First, we discuss how our system provides customized (virtualized) storage views within a single node. Then, we discuss how it scales in clustered setups. To achieve efficient resource and data sharing we support block-level allocation and locking as in-band mechanisms. We implement a prototype under Linux and use it to build a shared cluster file-system. Our evaluation in a 24-node cluster setup concludes that our approach offers flexibility, scalability and reduced effort to implement new functionality.

Lately, with increasing disk capacities, there is increased concern about protection from data errors, beyond masking of device failures. In this paper, we present a prototype I/O stack for storage controllers that encompasses two data protection features: (a) persistent checksums to protect data at-rest from silent errors and (b) block-level versioning to allow protection from user errors. Although these techniques have been previously used either at the device level (checksums) or at the host (versioning), in this work we implement these features in the storage controller, which allows us to use any type of storage devices as well as any type of host I/O stack. The main challenge in our approach is to deal with persistent metadata in the controller I/O path. Our main contribution is to show the implications of introducing metadata at this level and to deal with the performance issues that arise. Overall, we find that data protection features can be incorporated in the I/O path with a performance penalty in the range of 12% to 25%, offering much stronger data protection guarantees than today's commodity storage servers.

Flash-based solid state drives (SSDs) offer superior performance over hard disks for many workloads. A prominent use of SSDs in modern storage systems is to use these devices as a cache in the I/O path. In this work, we examine how transparent, online I/O compression can be used to increase the capacity of SSD-based caches, thus increasing the costeffectiveness of the system. We present FlaZ, an I/O system that operates at the block-level and is transparent to existing file-systems. To achieve transparent, online compression in the I/O path and maintain high performance, FlaZ, provides support for variable-size blocks, mapping of logical to physical blocks, block allocation, and cleanup. FlaZ, mitigates compression and decompression overheads that can have a significant impact on performance by leveraging modern multicore CPUs. We implement FlaZ, in the Linux kernel and evaluate it on a commodity server with multicore CPUs, using TPC-H, PostMark, and SPECsfs. Our results show that compressed caching trades off CPU cycles for I/O performance and enhances SSD efficiency as a cache by up to 99%, 25%, and 11% for each workload, respectively.

Retrieving sequential rich media content from modern commodity disks is a challenging task. As disk capacity increases, there is a need to increase the number of streams that are allocated to each disk. However, when multiple streams are accessing a single disk, throughput is dramatically reduced because of disk head seek overhead, resulting in requirements for more disks. Thus, there is a tradeoff between how many streams should be allowed to access a disk and the total throughput that can be achieved. In this work we examine this tradeoff and provide an understanding of issues along with a practical solution. We use Disksim, a detailed architectural simulator, to examine several aspects of a modern I/O subsystem and we show the effect of various disk parameters on system performance under multiple sequential streams. Then, we propose a solution that dynamically adjusts I/O request streams, based on host and I/O subsystem parameters. We implement our approach in a real system and perform experiments with a small and a large disk configuration. Our approach improves disk throughput up to a factor of 4 with a workload of 100 sequential streams, without requiring large amounts of memory on the storage node. Moreover, it is able to adjust (statically) to different storage node configurations, essentially making the I/O subsystem insensitive to the number of I/O streams used.

Volunteer computing is becoming a new paradigm not only for the computational grid, but also for institutions using production-level data grids because of the enormous storage potential that may be achieved at a low cost by using commodity hardware within their own computing premises. However, this novel "Desktop Data Grid" depends on a set of widely distributed and untrusted storage nodes, therefore offering no guarantees about neither availability nor protection to the stored data. These security challenges must be carefully managed before fully deploying desktop data grids in sensitive environments (such as eHealth) to cope with a broad range of storage needs, including backup and caching. In this paper we propose a cryptographic protocol able to fulfil the storage security requirements related with a generic desktop data grid scenario, which were identified after applying an analysis framework extended from our previous research on the data grid's storage services. The proposed protocol uses three basic mechanisms to accomplish its goal: (a) symmetric cryptography and hashing, (b) an information dispersal algorithm and the novel (c) "quality of security" (QoSec) quantitative metric. Although the focus of this work is the associated protocol, we also present an early evaluation using an analytical model. Our results show a strong relationship between the assurance of the data at rest, the QoSec of the volunteer storage client and the number of fragments required to rebuild the original file.

With the wide-spread deployment of Data Grid installations, and rapidly increasing data volumes, storage services are becoming a critical aspect of the Grid infrastructure. Due to the distributed and shared nature of the Grid, security issues related with state of the art data storage services need to be studied thoroughly to identify potential vulnerabilities and attack vectors. In this paper, motivated by a typical use-case for Data Grid storage, we apply an extended framework for analyzing and evaluating its security from the point of view of the data and metadata, taking into consideration the security capabilities provided by both the underlying Grid infrastructure and commonly deployed Grid storage systems. For a comprehensive analysis of the latter, we identify three important elements: the players being involved, the underlying trust assumptions and the dependencies on specic security primitives. This analysis leads to the identication of a set of potential security gaps, risks, and even redundant security features found in a typical Data Grid. These results are now the starting point for our ongoing research on policies and mechanisms able to provide a fair balance between security and performance for Data Grid Storage Services.

Distributed storage systems are expected to serve a broad spectrum of applications, satisfying various requirements with respect to capacity, speed, reliability, security at low cost. Virtualization techniques allow flexible configuration of storage systems in order to meet resource constraints and application requirements. Violin provides block level virtualization that enables the extension of storage with new mechanisms and combining them to create modular hierarchies. Creating and maintaining such virtualization hierarchies however, is a complex task where a human system administrator is the most expensive and less efficient element. We introduced Conductor, an automated support system that tries to grasp human expertise with declarative rules that are applied to storage management. So far the initial, static configuration capabilities of Conductor have been elaborated. Static features however, are not sufficient for practical purposes as the storage system evolves, i.e. requirements, workloads, access patterns may change in time. This paper presents work in progress that is aimed at extending Conductor with supporting dynamic features. We introduce the concepts of global and directed reconfigurations and discuss their potential strengths and weaknesses.

iSCSI is proposed as a possible solution to building future storage systems. However, using iSCSI raises numerous questions about its implications on system performance. This lack of understanding of system I/O behavior in modern and future systems inhibits providing solutions at the architectural and system levels. Our main goals in this work are to understand the behavior of the application server (iSCSI initiator), to evaluate the overhead introduced by iSCSI compared to systems with directly-attached storage, and to provide insight about how future storage systems may be improved. We examine these questions in the context of commodity iSCSI systems that can benefit most from using iSCSI. We use commodity PCs with several disks as storage nodes and a Gigabit Ethernet network as the storage network. On the application server side we use a broad range of benchmarks and applications to evaluate the impact of iSCSI on application and server performance. We instrument the Linux kernel to provide detailed information about I/O activity and the various overheads of kernel I/O layers. Our analysis reveals how iSCSI affects application performance and shows that building next generation, network-based I/O architectures, requires optimizing I/O latency, reducing network and buffer cache related processing in the host CPU, and increasing the sheer network bandwidth to account for consolidation of different types of traffic.

In this work we propose Violin, a virtualization framework that allows easy extensions of block-level storage stacks. Violin allows (i) developers to provide new virtualization functions and (ii) storage administrators to combine these functions in storage hierarchies with rich semantics. Violin makes it easy to develop such new functions by providing support for (i) hierarchy awareness and arbitrary mapping of blocks between virtual devices, (ii) explicit control over both the request and completion path of I/O requests, and (iii) persistent metadata management. To demonstrate the effectiveness of our approach we evaluate Violin in three ways: (i) we loosely compare the complexity of providing new virtual modules in Violin with the traditional approach of writing monolithic drivers. In many cases, adding new modules is a matter of recompiling existing user-level code that provides the required functionality. (ii) We show how simple modules in Violin can be combined in more complex hierarchies. We demonstrate hierarchies with advanced virtualization semantics that are difficult to implement with monolithic drivers. (iii) We use various benchmarks to examine the overheads introduced by Violin in the common I/O path. We find that Violin modules perform within 10% of the corresponding monolithic Linux drivers.