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...

We present an I/O architecture, called Swift, that addresses the problem of data rate mismatches between the requirements of an application, storage devices, and the interconnection medium. The goal of Swift is to support high data rates in general purpose distributed systems. Swift uses a high-speed interconnection medium to provide high data rate transfers by using multiple slower storage devices in parallel. It scales well when using multiple storage devices and interconnections, and can use any appropriate storage technology, including high-performance devices such as disk arrays. To address the problem of partial failures, Swift stores data redundantly. Using the UNIX operating system, we have constructed a simplified prototype of the Swift architecture. The prototype provides data rates that are significantly faster than access to the local SCSI disk, limited by the capacity of a single Ethernet segment, or in the case of multiple Ethernet segments by the ability of the client to drive them. We have constructed a simulation model to demonstrate how the Swift architecture can exploit advances in processor, communication and storage technology. We consider the effects of processor speed, interconnection capacity, and multiple storage agents on the utilization of the components and the data rate of the system. We show that the data rates scale well in the number of storage devices, and that by replacing the most highly stressed components by more powerful ones the data rates of the entire system increase significantly.

AFS plays a prominent role in our plans for a mobile workstation. The AFS client manages a cache of the most recently used files and directories. But even when the cache is hot, access to cached data frequently involves some communication with one or more file servers to maintain consistency guarantees. Without network access, cached data is soon rendered unavailable. We have modified the AFS cache manager to offer optimistic consistency guarantees when it can not communicate with a file server. When the client reestablishes a connection with the file server, it tries to propagate all file modifications to the server. If conflicts are detected, the replay agent notifies the user that manual resolution is needed. Our system brings the benefits of contemporary distributed computing environments to mobile laptops, offering a fresh look at the potential for nomadic computing.

. Current I/O benchmarks suffer from several chronic problems: they quickly become obsolete, they do not stress the I/O system, and they do not help in understanding I/O system performance. We propose a new approach to I/O performance analysis. First, we propose a self-scaling benchmark that dynamically adjusts aspects of its workload according to the performance characteristic of the system being measured. By doing so, the benchmark automatically scales across current and future systems. The evaluation aids in understanding system performance by reporting how performance varies according to each of five workload parameters. Second, we propose predicted performance, a technique for using the results from the self-scaling evaluation to quickly estimate the performance for workloads that have not been measured. We show that this technique yields reasonably accurate performance estimates and argue that this method gives a far more accurate comparative performance evaluation than tradition...

RPC latencies and other network-related delays can frustrate mobile users of a distributed file system. Disconnected operation helps, but fails to use networking opportunities to their full advantage. In this paper we describe partially connected operation, an extension of disconnected operation that resolves cache misses and preserves client cache consistency, but does not incur the write latencies of a fully connected client. Benchmarks of partially connected mode over a slow network indicate overall system performance comparable to fully connected operation over Ethernet.

In this paper, we propose a new adaptive buffer management scheme called DEAR (DEtection based Adaptive Replacement) that automatically detects the block reference patterns of applications and applies different replacement policies to different applications based on the detected reference pattern. The proposed DEAR scheme uses a periodic process. Detection is made by associating block attribute values such as backward distance and frequency gathered at the (i \Gamma 1)-th invocation with forward distances of blocks referenced between the (i \Gamma 1)-th and i-th invocations. We implemented the DEAR scheme in FreeBSD 2.2.5 and measured its performance using several real applications. The results show that compared with the LRU buffer management scheme, the proposed scheme reduces the number of disk I/Os by up to 51% (with an average of 23%) and the response time by up to 35% (with an average of 12%) in the case of single application executions. For multiple applications, the proposed sc...

To overcome availability, latency, bandwidth, and cost barriers of mobile networks, mobile clients of distributed file systems switch between connected and disconnected modes of operation. Lying between these are modes of operation that refine the consistency semantics of cached files, allowing a mobile client to select a mode appropriate for the the prevailing network conditions. Clients can take advantage of network opportunities unsuitable for connected operation, obtaining improved performance, more effective sharing, and more stringent consistency guarantees as a result.

Introduction Continued improvements in processor performance have exposed I/O subsystems as a significant bottleneck, which prevents applications from achieving full system utilization [33, 54]. This problem is exacerbated in massively parallel processors (MPPs), where multiple processors are used together. As a result, I/O subsystems have become the focus of much research, leading to the design of parallel I/O hardware and matching system software. The requirement driving the work on I/O subsystems is the desire to achieve a balanced system [8]. The degree to which a system is balanced is typically expressed by the F=b ratio, which is defined as the ratio of the rate of executing floating point operations (F ) to the rate of performing I/O, in bits per second (b). A widely accepted rule of thumb, attributed to Amdahl, calls for F=b 1. While this was originally expressed in instructions rather than floating po

We consider file system operation in a transparently fault-tolerant system that uses checkpointing and message logging. Logging messages to disk is one of the primary performance costs of such systems. We have measured the file system operations performed on large timesharing systems running Unix in terms of the level of concurrency (number of consecutive operations by the same process) and the read ratio (number of operations that do not change the state of the file system). By performing much of the data analysis on-line within a modified Unix kernel, we were able to collect statistics over a long period of time with a substantial variation in system load. Using this data, we demonstrate that a technique we call null logging can reduce the number of messages logged to disk by a factor of 10 to 25, depending on the workload. This reduces the overhead of the faulttolerance mechanism and also allows a large fraction of file system operations to commit instantaneously. 1 Introduction ...

A new buffer replacement scheme called DEAR (DEtection-based Adaptive Replacement) is presented for effective caching of disk blocks in the operating system. The proposed DEAR scheme automatically detects block reference patterns of applications and applies different replacement policies to different applications depending on the detected reference pattern. The detection is made by a periodic process and is based on the relationship between block attribute values such as backward distance and frequency gathered in a period and the forward distance observed in the next period. This paper also describes an implementation and performance measurement of the DEAR scheme in FreeBSD. The results from performance measurements of several real applications show that compared with the LRU scheme, the proposed scheme reduces the number of disk I/Os by up to 51% (with an average of 23%) and the response time by up to 35% (with an average of 12%) in the case of single application execution...