Configuring redundant disk arrays is a black art. To configure an array properly, a system administrator must understand the details of both the array and the workload it will support. Incorrect understanding of either, or changes in the workload over time, can lead to poor performance. We present a solution to this problem: a two-level storage hierarchy implemented inside a single diskarray controller. In the upper level of this hierarchy, two copies of active data are stored to provide full redundancy and excellent performance. In the lower level, RAID 5 parity protection is used to provide excellent storage cost for inactive data, at somewhat lower performance. The technology we describe in this paper, known as HP AutoRAID, automatically and transparently manages migration of data blocks between these two levels as access patterns change. The result is a fully redundant storage system that is extremely easy to use, is suitable for a wide variety of workloads, is largely insensitive to dynamic workload changes, and performs much better than disk arrays with comparable numbers of spindles and much larger amounts of front-end RAM cache. Because the implementation of the HP AutoRAID technology is almost entirely in software, the additional hardware cost for these benefits is very small. We describe the HP AutoRAID technology in detail, provide performance data for an embodiment of it in a storage array, and summarize the results of simulation studies used to choose algorithms implemented in the array.

It is well-known that Reed-Solomon codes may be used to provide error correction for multiple failures in RAID-like systems. The coding technique itself, however, is not as well-known. To the coding theorist, this technique is a straightforward extension to a basic coding paradigm and needs no special mention. However, to the systems programmer with no training in coding theory, the technique may be a mystery. Currently, there are no references that describe how to perform this coding that do not assume that the reader is already well-versed in algebra and coding theory. This paper is intended for the systems programmer. It presents a complete specification of the coding algorithm plus details on how it may be implemented. This specification assumes no prior knowledge of algebra or coding theory. The goal of this paper is for a systems programmer to be able to implement Reed-Solomon coding for reliability in RAID-like systems without needing to consult any external references. Problem Specification Let there be storage devices, ¡£¢¥¤¦¡¨§©¤�������¤¦¡¨�, each of which holds � bytes. These are called the “Data De-vices. ” � Let there be � � more storage devices

Current operating systems offer poor performance when a numeric application's working set does not fit in main memory. As a result, programmers who wish to solve "out-of-core" problems efficiently are typically faced with the onerous task of rewriting an application to use explicit I/O operations (e.g., read/write). In this paper, we propose and evaluate a fully-automatic technique which liberates the programmer from this task, provides high performance, and requires only minimal changes to current operating systems. In our scheme, the compiler provides the crucial information on future access patterns without burdening the programmer, the operating system supports non-binding prefetch and re- lease hints for managing I/O, and the operating sys- tem cooperates with a run-time layer to accelerate performance by adapting to dynamic behavior and minimizing prefetch overhead. This approach maintains the abstraction of unlimited virtual memory for the programmer, gives the compiler the flexibility to aggressively move prefetches back ahead of references, and gives the operating system the flexibility to arbitrate between the competing resource demands of multiple applications. We have implemented our scheme using the SUIF compiler and the Hurricane operating system. Our experimental results demonstrate that our fully-automatic scheme effectively hides the I/O latency in out-of- core versions of the entire NAS Parallel benchmark suite, thus resulting in speedups of roughly twofold for five of the eight applications, with one application speeding up by over threefold.

Diskless Checkpointing is a technique for checkpointing the state of a long-running computation on a distributed system without relying on stable storage. As such, it eliminates the performance bottleneck of traditional checkpointing on distributed systems. In this paper, we motivate diskless checkpointing and present the basic diskless checkpointing scheme along with several variants for improved performance. The performance of the basic scheme and its variants is evaluated on a high-performance network of workstations and compared to traditional disk-based checkpointing. We conclude that diskless checkpointing is a desirable alternative to disk-based checkpointing that can improve the performance of distributed applications in the face of failures.

This paper describes the motivation, design, and performance of Porcupine, a scalable mail server. The goal of Porcupine is to provide a highly available and scalable electronic mail service using a large cluster of commodity PCs. We designed Porcupine to be easy to manage by emphasizing dynamic load balancing, automatic configuration, and graceful degradation in the presence of failures. Key to the system’s manageability, availability, and performance is that sessions, data, and underlying services are distributed homogeneously and dynamically across nodes in a cluster.

This paper describes the design, implementation, and evaluation of a Federated Array of Bricks (FAB), a distributed disk array that provides the reliability of traditional enterprise arrays with lower cost and better scalability. FAB is built from a collection of bricks, small storage appliances containing commodity disks, CPU, NVRAM, and network interface cards. FAB deploys a new majority-votingbased algorithm to replicate or erasure-code logical blocks across bricks and a reconfiguration algorithm to move data in the background when bricks are added or decommissioned. We argue that voting is practical and necessary for reliable, high-throughput storage systems such as FAB. We have implemented a FAB prototype on a 22-node Linux cluster. This prototype sustains 85MB/second of throughput for a database workload, and 270MB/second for a bulk-read workload. In addition, it can outperform traditional masterslave replication through performance decoupling and can handle brick failures and recoveries smoothly without disturbing client requests.

This paper discusses the application of end-to-end design principles, which are characteristic of the architecture of the Internet, to network storage. While putting storage into the network fabric may seem to contradict end-to-end arguments, we try to show not only that there is no contradiction, but also that adherence to such an approach is the key to achieving true scalability of shared network storage. After discussing end-to-end arguments with respect to several properties of network storage, we describe the Internet Backplane Protocol and the exNode, which are tools that have been designed to create a network storage substrate that adheres to these principles. The name for this approach is Logistical Networking, and we believe its use is fundamental to the future of truly scalable communication.

This paper presents a novel disk storage architecture called DCD, Disk Caching Disk, for the purpose of optimizing I/O performance. The main idea of the DCD is to use a small log disk, referred to as cache-disk, as a secondary disk cache to optimize write performance. While the cache-disk and the normal data disk have the same physical properties, the access speed of the former differs dramatically from the latter because of different data units and different ways in which data are accessed. Our objective is to exploit this speed difference by using the log disk as a cache to build a reliable and smooth disk hierarchy. A small RAM buffer is used to collect small write requests to form a log which is transferred onto the cache-disk whenever the cache-disk is idle. Because of the temporal locality that exists in office/engineering work-load environments, the DCD system shows write performance close to the same size RAM (i.e. solid-state disk) for the cost of a disk. Moreover, the cache...

With the increasing popularity of portable wireless computers, mechanisms to efficiently transmit information to such clients are of significant interest. The environment under consideration is asymmetric in that the information server has much more bandwidth available, as compared to the clients. In such environments, often it is not possible (or not desirable) for the clients to send explicit requests to the server. It has been proposed that in such systems the server should broadcast the data periodically. One challenge in implementing this solution is to determine the schedule for broadcasting the data, such that the wait encountered by the clients is minimized. A broadcast schedule determines what is broadcast by the server and when. In this report, we present algorithms for determining broadcast schedules that minimize the wait time. Simulation results are presented to demonstrate that our algorithms perform well. Variations of our algorithms for environments subject to errors, and systems where different clients may listen to different number of broadcast channels are also considered.

Track-aligned extents (traxtents) utilize disk-specific knowledge to match access patterns to the strengths of modern disks. By allocating and accessing related data on disk track boundaries, a system can avoid most rotational latency and track crossing overheads. Avoiding these overheads can increase disk access efficiency by up to 50 % for mid-sized requests (100-500 KB). This paper describes traxtents, algorithms for detecting track boundaries, and some uses of traxtents in file systems and video servers. For large-file workloads, a version of FreeBSD's FFS implementation that exploits traxtents reduces application run times by up to 20 % compared to the original version. A video server using traxtent-based requests can support 56 % more concurrent streams at the same startup latency and buffer space. For LFS, 44 % lower overall write cost for track-sized segments can be achieved.