Since the invention of the movable head disk, people have improved I/O performance by intelligent scheduling of disk accesses. We have applied these techniques to systems with large memories and potentially long disk queues. By viewing the entire buffer cache as a write buffer, we can improve disk bandwidth utilization by applying some traditional disk scheduling techniques. We have analyzed these techniques, which attempt to optimize head movement and guarantee fairness in response time, in the presence of long disk queues. We then propose two algorithms which take rotational latency into account, achieving disk bandwidth utilizations of nearly four times a simple first come first serve algorithm. One of these two algorithms, a weighted shortest total time first, is particularly applicable to a file server environment because it guarantees that all requests get to disk within a specified time window. 1.

In this paper, we present the Cello disk scheduling framework for meeting the diverse service requirements of applications. Cello employs a two-level disk scheduling architecture, consisting of a classindependent scheduler and a set of class-specific schedulers. The two levels of the framework allocate disk bandwidth at two timescales: the class-independent scheduler governs the coarse-grain allocation of bandwidth to application classes, while the class-specific schedulers control the fine-grain interleaving of requests. The two levels of the architecture separate application-independent mechanisms from application-specific scheduling policies, and thereby facilitate the co-existence of multiple class-specific schedulers. We demonstrate that Cello is suitable for next generation operating systems since: (i) it aligns the service provided with the application requirements, (ii) it protects application classes from one another, (iii) it is work-conserving and can adapt to changes in wor...

cupertino California Disk shadowing is a technique for maintaining a set of two or more identical disk images on separate disk devices. Its primary purpose is to enhance reliability and availability of secondary storage by providing multiple paths to redundant data. However, shadowing can also boost UO performance. In this paper, we contend that intelligent device scheduling of shadowed disks increases the I/O rate, by allowing parallel reads and by substantially reducing the average seek time for random reads. In particular, we develop an analytic model which shows that the seek time for a random read in a shadow set is a monotonic decreasing function of the number of disks in the set. 1.

Disk subsystem performance can be dramatically improved by dynamically ordering, or scheduling, pending requests. Via strongly validated simulation, we examine the impact of complex logical-to-physical mappings and large prefetching caches on scheduling effectiveness. Using both synthetic workloads and traces captured from six different user environments, we arrive at three main conclusions: (1) Incorporating complex mapping information into the scheduler provides only a marginal (less than 2%) decrease in response times for seek-reducing algorithms. (2) Algorithms which effectively utilize prefetching disk caches provide significant performance improvements for workloads with read sequentiality. The cyclical scan algorithm (C-LOOK), which always schedules requests in ascending logical order, achieves the highest performance among seek-reducing algorithms for such workloads. (3) Algorithms that reduce overall positioning delays produce the highest performance provided that they recogni...

A large-scale multimedia server, in practice, has to service a large number of clients simultaneously. Given the real-time requirements of each client and the fixed data transfer bandwidth of disks, a multimedia server must employ admission control algorithms to decide whether a new client can be admitted for service without violating the requirements of the clients already being serviced. In this paper, we present an admission control algorithm for multimedia servers which: (1) exploits the variation in access times of media blocks from disk as well as the variation in client load induced by variable rate compression schemes, and (2) provides statistical service guarantees to each client. The effectiveness of the algorithm is demonstrated through trace-driven simulations.

A continuum of disk scheduling algorithms, V(R), having endpoints V(0) = SSTF and V(1) = SCAN, is defined. V(R) maintains a current SCAN direction (in or out) and services next the request with the smallest effective distance. The effective distance of a request that lies in the current direction is its physical distance (in cylinders) from the read/write head. The effective distance of a request in the opposite direction is its physical distance plus R X (total number of cylinders on the disk). By use of simulation methods, it is shown that this definitional continuum also provides a continuum in performance, both with respect to the mean and with respect to the standard deviation of request waiting time. For objective functions that are linear combinations of the two measures, pw + kuw, intermediate points of the continuum are seen to provide performance uniformly superior to both SSTF and SCAN. A method of implementing V(R) and the results of its experimental use in a real system are presented.

A variety of performance-enhancing techniques, such as striping, mirroring, and rotational data replication, exist in the disk array literature. Given a fixed budget of disks, one must intelligently choose which and what combination of these techniques to employ. In this paper, we present a way of designing disk arrays that can flexibly and systematically reduce seek and rotational delay in a balanced manner. We give analytical models that can guide an array designer towards optimal configurations by considering both disk and workload characteristics. We have implemented a prototype disk array that incorporates the configuration models. In the process, we have also developed a robust disk head position prediction mechanism without any hardware support. The resulting prototype demonstrates the e#ectiveness of the configuration models. 1

Modern disk drives read-ahead data and reorder incoming requests in a workload-dependent fashion. This improves their performance, but makes simple analytical models of them inadequate for performance prediction, capacity planning, workload balancing, and so on. To address this problem we have developed a new analytic model for disk drives that do readahead and request reordering. We did so by developing performance models of the disk drive components (queues, caches, and the disk mechanism) and a workload transformation technique for composing them. Our model includes the effects of workload-specific parameters such as request size and spatial locality. The result is capable of predicting the behavior of a variety of real-world devices to within 17% across a variety of workloads and disk drives.

Although object-oriented database systems offer advantages over relational or record-oriented database systems, such as modeling facilities for complex objects, they are criticized for poor performance and query capabilities on set-oriented applications. The unacceptable performance is due in part to the object-at-a-time processing typically used by object-oriented database systems. We believe that improved performance of object-oriented database systems depends partially on the efficient and selective retrieval of sets of complex objects from secondary storage. In this report, we present the method of complex object retrieval and assembly used in the Volcano query processing system and the Revelation project. We also present experimental results comparing set-oriented versus object-at-a-time complex object assembly. 1. Introduction Relational database management systems provide a simple and well-understood model of data. The simplicity and theory of the relational model result in eff...

In a chip-multiprocessor (CMP) system, the DRAM system is shared among cores. In a shared DRAM system, requests from a thread can not only delay requests from other threads by causing bank/bus/row-buffer conflicts but they can also destroy other threads’ DRAM-bank-level parallelism. Requests whose latencies would otherwise have been overlapped could effectively become serialized. As a result both fairness and system throughput degrade, and some threads can starve for long time periods. This paper proposes a fundamentally new approach to designing a shared DRAM controller that provides quality of service to threads, while also improving system throughput. Our parallelism-aware batch scheduler (PAR-BS) design is based on two key ideas. First, PAR-BS processes DRAM requests in batches to provide fairness and to avoid starvation of requests. Second, to optimize system throughput, PAR-BS employs a parallelism-aware DRAM scheduling policy that aims to process requests from a thread in parallel in the DRAM banks, thereby reducing the memory-related stall-time experienced by the thread. PAR-BS seamlessly incorporates support for system-level thread priorities and can provide different service levels, including purely opportunistic service, to threads with different priorities. We evaluate the design trade-offs involved in PAR-BS and compare it to four previously proposed DRAM scheduler designs on 4-, 8-, and 16-core systems. Our evaluations show that, averaged over 100 4-core workloads, PAR-BS improves fairness by 1.11X and system throughput by 8.3 % compared to the best previous scheduling technique, Stall-Time Fair Memory (STFM) scheduling. Based on simple request prioritization rules, PAR-BS is also simpler to implement than STFM.