2306737
Managing flash crowds on the Internet
A flash crowd is a surge in traffic to a particular Web site that causes the site to be virtually unreachable. We present a model of flash crowd events and evaluate the performance of various multilevel caching techniques suitable for managing these events. By using well-dispersed caches and with judicious choice of replacement algorithms we show reductions in client response times by as much as a factor of 25. We also show that these caches eliminate the server and network hot spots by distributing the load over the entire network.
13755993
Zone-based shortest positioning time first scheduling for MEMS-based storage devices
Access latency to secondary storage devices is frequently a limiting factor in computer system performance. New storage technologies promise to provide greater storage densities at lower latencies than is currently obtainable with hard disk drives. MEMS-based storage devices use orthogonal magnetic or physical recording techniques and thousands of simultaneously active MEMS-based read-write tips to provide high-density low-latency nonvolatile storage. These devices promise seek times 10-20 times faster than hard drives, storage densities 10 times greater, and power consumption an order of magnitude lower. Previous research has examined data layout and request ordering algorithms that are analogs of those developed for hard drives. We present an analytical model of MEMS device performance that motivates a computationally simple MEMS-based request scheduling algorithm called ZSPTF, which has average response times comparable to shortest positioning time first (SPTF) but with response time variability comparable to circular scan (C-SCAN).
8965925
Power conservation strategies for MEMS-based storage devices
Power dissipation by storage systems in mobile computers accounts for a large percentage of the power consumed by the entire system. Reducing the power used by the storage device is crucial for reducing overall power consumption. A new class of secondary storage devices based on microelectromechanical systems (MEMS) promises to consume an order of magnitude less power with 10-20 times shorter latency and 10 times greater storage densities. We describe three strategies to reduce power consumption: aggressive spin-down; sequential request merging; sub-sector accesses. We show that aggressive spin-down can save up to 50% of the total energy consumed by the device at the cost of increased response time. Merging of sequential requests can save up to 18% of the servicing energy and reduce response time by about 20%. Transferring less data for small requests such as those for metadata can save 40% of the servicing energy. Finally, we show that by applying all three power management strategies simultaneously the total power consumption of MEMS-based storage devices can be reduced by about 54% with no impact on I/O performance.
2398128
Design and Implementation of a Predictive File Prefetching Algorithm
We have previously shown that the patterns in which files are accessed offer information that can accurately predict upcoming file accesses. Most modern caches ignore these patterns, thereby failing to use information that enables significant reductions in I/O latency. While prefetching heuristics that expect sequential accesses are often effective methods to reduce I/O latency, they cannot be applied across files, because the abstraction of a file has no intrinsic concept of a successor. This limits the ability of modern file systems to prefetch. Here we presents our implementation of a predictive prefetching system, that makes use of file access patterns to reduce I/O latency. Previously we developed a technique called Partitioned Context Modeling (PCM) [13] that efficiently models file accesses to reliably predict upcoming requests. We present our experiences in implementing predictive prefetching based on file access patterns. From the lessons learned we developed of a new technique Extended Partitioned Context Modeling (EPCM), which has even better performance. We have modified the Linux kernel to prefetch file data based on Partitioned Context Modeling and Extended Partitioned Context Modeling. With this implementation we examine how a prefetching policy, that uses such models to predict upcoming accesses, can result in large reductions in I/O latencies. We tested our implementation with four different application-based benchmarks and saw I/O latency reduced by 31% to 90% and elapsed time reduced by 11% to 16%. tmk@cips.nokia.com. Supported in part by the Usenix Association and the National Science Foundation under Grant CCR-9704347. darrell@cse.ucsc.edu. Supported in part by the National Science Foundation under Grant CCR-9704347.
415554
Disk scrubbing in large archival storage systems
Large archival storage systems experience long periods of idleness broken up by rare data accesses. In such systems, disks may remain powered off for long periods of time. These systems can lose data for a variety of reasons, including failures at both the device level and the block level. To deal with these failures, we must detect them early enough to be able to use the redundancy built into the storage system. We propose a process called "disk scrubbing" in a system in which drives are periodically accessed to detect drive failure. By scrubbing all of the data stored on all of the disks, we can detect block failures and compensate for them by rebuilding the affected blocks. Our research shows how the scheduling of disk scrubbing affects overall system reliability, and that "opportunistic" scrubbing, in which the system scrubs disks only when they are powered on for other reasons, performs very well without the need to power on disks solely to check them.
5159428
Ceph: a scalable, high-performance distributed file system
We have developed Ceph, a distributed file system that provides excellent performance, reliability, and scalability. Ceph maximizes the separation between data and metadata management by replacing allocation tables with a pseudo-random data distribution function (CRUSH) designed for heterogeneous and dynamic clusters of unreliable object storage devices (OSDs). We leverage device intelligence by distributing data replication, failure detection and recovery to semi-autonomous OSDs running a specialized local object file system. A dynamic distributed metadata cluster provides extremely efficient metadata management and seamlessly adapts to a wide range of general purpose and scientific computing file system workloads. Performance measurements under a variety of workloads show that Ceph has excellent I/O performance and scalable metadata management, supporting more than 250,000 metadata operations per second.
2816085
Maximum entropy image restoration revisited
This paper presents a new non-iterative, closed-form approximation to the maximum entropy (ME) image restoration method. A fast frequency domain implementation of this closed form approach is developed for the case of circular convolutional blur. This result dramatically reduces the computational demands compared to conventional iterative ME algorithms such as MART. Some limitations and advantages of ME restoration are investigated, including its dismal performance for high resolution restoration of decimated or randomly sampled blurred observations.
3125175
A dynamic heuristic broadcasting protocol for video-on-demand
Most existing distribution protocols for video-on-demand are tailored for a specific range of video access rates and perform poorly beyond that range. We present a dynamic heuristic broadcasting protocol that performs as well as stream tapping with unlimited extra tapping at low video access rates and has the same average bandwidth requirements as the best existing broadcasting protocols at high video access rates. We also show how our protocol can handle compressed video and adapt itself to the individual bandwidth requirements of each video.
5757820
Persuasion as a Form of Inter-Agent Negotiation
Agents in a multi-agent environment must often cooperate to achieve their objectives. In this paper an agent, B, cooperates with another agent, A, if B adopts a goal that furthers A's objectives in the environment. If agents are independent and motivated by their own interests, cooperation cannot be relied upon and it may be necessary for A to persuade B to adopt a cooperative goal. This paper is concerned with the organisation and construction of persuasive argument, and examines how a rational agent comes to hold a belief, and thus, how new beliefs might be engendered and existing beliefs altered, through the process of argumentation. Argument represents an opportunity for an agent to convince a possibly sceptical or resistant audience of the veracity of its own beliefs. This ability is a vital component of rich communication, facilitating explanation, instruction, cooperation and conflict resolution. An architecture is described in which a hierarchical planner is used to develop discourse plans which can be realised in natural language using the LOLITA system. Planning is concerned with the intentional, contextual and pragmatic aspects of discourse structure as well as with the logical form of the argument and its stylistic organisation. In this paper attention is restricted to the planning of persuasive discourse, or monologue.