Emerging high-speed networks will allow machines to access remote data nearly as quickly as they can access local data. This trend motivates the use of cooperative caching: coordinating the file caches of many machines distributed on a LAN to form a more effective overall file cache. In this paper we examine four cooperative caching algorithms using a trace-driven simulation study. These simulations indicate that for the systems studied cooperative caching can halve the number of disk accesses, improving file system read response time by as much as 73%. Based on these simulations we conclude that cooperative caching can significantly improve file system read response time and that relatively simple cooperative caching algorithms are sufficient to realize most of the potential performance gain.

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.

Minimizing power consumption is important for mobile computers, and disks consume a significant portion of system-wide power. There is a large difference in power consumption between a disk that is spinning and one that is not, so systems try to keep the disk spinning only when it must. The system must trade off between the power that can be saved by spinning the disk down quickly after each access and the impact on response time from spinning it up again too often. We use trace-driven simulation to examine these trade-offs, and compare a number of different algorithms for controlling disk spin-down. We simulate disk accesses from a mobile computer (a Macintosh Powerbook Duo 230) and also from a desktop workstation (a Hewlett-Packard 9000/845 personal workstation running HP-UX), running on two disks used on mobile computers, the Hewlett-Packard Kittyhawk C3014A and the Quantum Go Drive 120. We show that the "perfect" off-line algorithm|one that consumes minimum power without increasing response time relative to a disk that never spins down -- can reduce disk power consumption by 35-50%, compared to the xed threshold suggested by manufacturers. An on-line algorithm with a threshold of 10 seconds, running on the Powerbook trace and Go Drive disk, reduces energy consumption by about 40 % compared to the the 5-minute threshold recommended by manufacturers of comparable disks; however, over a 4-hour trace period it results in 140 additional delays due to disk spin-ups.

We address the problem of deciding when to spin down the disk of a mobile computer in order to extend battery life. Since one of the most critical resources in mobile computing environments is battery life, good energy conservation methods can dramatically increase the utility of mobile systems. We use a simple and efficient algorithm based on machine learning techniques that has excellent performance in practice. Our experimental results are based on traces collected from HP C2474s disks. Using this data, the algorithm outperforms several algorithms that are theoretically optimal in under various worst-case assumptions, as well as the best fixed time-out strategy. In particular, the algorithm reduces the power consumption of the disk to about half (depending on the disk's properties) of the energy consumed by a one minute fixed time-out. Since the algorithm adapts to usage patterns, it uses as little as 88% of the energy consumed by the best fixed time-out computed in retrospect. 1 In...

With the advent and subsequent popularity of portable computers, power management of system components has become an important issue. Current portable computers implement anumber of power reduction techniques to achieve a longer battery life. Included among these is spinning down a disk during long periods of inactivity. In this paper, we perform a quantitative analysis of the potential costs and bene ts of spinning down the disk drive as apower reduction technique. Our conclusion is that almost all the energy consumed by a disk drive can be eliminated with little loss in performance. Although on current hardware, reliability can be impacted by our policies, the next generation of disk drives will use technology (such as dynamic head loading) which is virtually una ected by repeated spinups. We found that the optimal spindown delay time, the amount of time the disk idles before it is spun down, is 2 seconds. This di ers signi cantly from the 3-5 minutes in current practice by industry. We will show in this paper the e ect of varying the spindown delay onpower consumption � one conclusion is that a 3-5 minute delay results in only half of the potential bene t of spinning down a disk. 1

Many people have observed that computer systems spend much of their time idle, and various schemes have been proposed to use this idle time productively. The commonest approach is to off-load activity from busy periods to less-busy ones in order to improve system responsiveness. In addition, speculative work can be performed in idle periods in the hopes that it will be needed later at times of higher utilization, or non-renewable resource like battery power can be conserved by disabling unused resources. We found opportunities to exploit idle time in our work on storage systems, and after a few attempts to tackle specific instances of it in ad hoc ways, began to investigate general mechanisms that could be applied to this problem. Our results include a taxonomy of idle-time detection algorithms, metrics for evaluating them, and an evaluation of a number of idleness predictors that we generated from our taxonomy. 1. Introduction Resource usage is often bursty: periods of high utilizat...

A large portion of the power budget in server environments goes into the I/O subsystem- the disk array in particular. Traditional approaches to disk power management involve completely stopping the disk rotation, which can take a considerable amount of time, making them less useful in cases where idle times between disk requests may not be long enough to outweigh the overheads. This paper presents a new approach called DRPM to modulate disk speed (RPM) dynamically, and gives a practical implementation to exploit this mechanism. Extensive simulations with different workload and hardware parameters show that DRPM can provide significant energy savings without compromising much on performance. This paper also discusses practical issues when implementing DRPM on server disks. Keywords: Server Disks, Power Management. 1

This paper describes the architecture of eNVy, a large non-volatile main memory storage system built primarily with Flash memory. eNVy presents its storage space as a linear, memory mapped array rather than as an emulated disk in order to provide an efficient and easy to use software interface. Flash memories...

The Logical Disk (LD) defines a new interface to disk storage that separates file management and disk management by using logical block numbers and block lists. The LD interface is designed to support multiple file systems and to allow multiple implementations, both of which are important given the increasing use of kernels that support multiple operating system personalities. A log-structured implementation of LD (LLD) demonstrates that LD can be implemented efficiently. LLD adds about 5% to 10% to the purchase cost of a disk for the main memory it requires. Combining LLD with an existing file system results in a log-structured file system that exhibits the same performance characteristics as the Sprite log-structured file system.

Enterprise-scale storage systems, which can contain hundreds of host computers and storage devices and up to tens of thousands of disks and logical volumes, are difficult to design. The volume of choices that need to be made is massive, and many choices have unforeseen interactions. Storage system design is tedious and complicated to do by hand, usually leading to solutions that are grossly overprovisioned, substantially under-performing or, in the worst case, both. To solve the configuration nightmare, we present MINERVA: a suite of tools for designing storage systems automatically. MINERVA uses declarative specifications of application requirements and device capabilities; constraint-based formulations of the various subproblems; and optimization techniques to explore the search space of possible solutions. This paper also explores and evaluates the design decisions that went into MINERVA, using specialized micro and macro-benchmarks. We show that MINERVA can successfully handle a workload with substantial complexity (a decision-support database benchmark). MINERVA created a 16-disk design in only a few minutes that achieved the same performance as a 30-disk system manually designed by human experts. Of equal importance, MINERVA was able to predict the resulting system's performance before it was built.