Synchronized Disk Interleaving
IEEE Transactions on Computers
An Evaluation of Multiple-Disk I/O Systems
IEEE Transactions on Computers
Practical prefetching via data compression
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
RAID: high-performance, reliable secondary storage
ACM Computing Surveys (CSUR)
Sequentiality and prefetching in database systems
ACM Transactions on Database Systems (TODS)
Maximizing performance in a striped disk array
ISCA '90 Proceedings of the 17th annual international symposium on Computer Architecture
A cost-benefit scheme for high performance predictive prefetching
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Compiler-Directed I/O Optimization
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Analysis of Non-Work-Conserving Processor Partitioning Policies
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Noncontiguous I/O Accesses Through MPI-IO
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Data Sieving and Collective I/O in ROMIO
FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
An Analytic Performance Model of Disk Arrays And Its Application
An Analytic Performance Model of Disk Arrays And Its Application
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Automatic ARIMA Time Series Modeling for Adaptive I/O Prefetching
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the twentieth ACM symposium on Operating systems principles
C-Miner: Mining Block Correlations in Storage Systems
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
The automatic improvement of locality in storage systems
ACM Transactions on Computer Systems (TOCS)
Aggressive prefetching: an idea whose time has come
HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
Antfarm: tracking processes in a virtual machine environment
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Argon: performance insulation for shared storage servers
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
DiskSeen: exploiting disk layout and access history to enhance I/O prefetch
ATC'07 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference
Improving I/O performance of applications through compiler-directed code restructuring
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
On the design of a new Linux readahead framework
ACM SIGOPS Operating Systems Review - Research and developments in the Linux kernel
Availability and Fairness Support for Storage QoS Guarantee
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
BORG: block-reORGanization for self-optimizing storage systems
FAST '09 Proccedings of the 7th conference on File and storage technologies
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Co-scheduling of Disk Head Time in Cluster-Based Storage
SRDS '09 Proceedings of the 2009 28th IEEE International Symposium on Reliable Distributed Systems
Does virtualization make disk scheduling passé?
ACM SIGOPS Operating Systems Review
InterferenceRemoval: removing interference of disk access for MPI programs through data replication
Proceedings of the 24th ACM International Conference on Supercomputing
I/O deduplication: utilizing content similarity to improve I/O performance
FAST'10 Proceedings of the 8th USENIX conference on File and storage technologies
IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Survey and analysis of disk scheduling methods
ACM SIGARCH Computer Architecture News
A Prefetching Scheme Exploiting both Data Layout and Access History on Disk
ACM Transactions on Storage (TOS)
I/O scheduling in Android devices with flash storage
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
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Exploiting spatial locality is critical for a disk scheduler to achieve high throughput. Because of the high cost of disk head seeks and the non-preemptible nature of request service, state-of-the-art disk schedulers consider the locality of both pending and future requests. Though schedulers adopting the approach, such as the anticipatory scheduler, show substantial performance advantages, they need to know from which processes requests are issued to evaluate locality. This approach is not effective when the knowledge about processes is not available (e.g., in virtual machine environment, network or parallel file systems, and SAN) or the locality exhibited on a disk region is not solely determined by individual processes (e.g., in the case of cooperative process groups and disk array where requested data are striped). We propose a light-weight disk scheduling framework that does not require any process knowledge for analyzing request locality. Solely based on requests' own characteristics the framework can make any work-conserving scheduler non-work-conserving, i.e., able to take future requests as dispatching candidates, to fully exploit locality. Additionally, we show how to effectively extend the framework to the disk array environment. Our design, Stream Scheduling, is prototyped in the Linux kernel 2.6.31. With extensive experiments of representative benchmarks, and in various environments such as the Xen virtual machine and the PVFS parallel file system, we show that the proposed scheduling framework can improve their performance by up to 3.2 times.