Disconnected operation in the Coda file system
SOSP '91 Proceedings of the thirteenth ACM symposium on Operating systems principles
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Automated hoarding for mobile computers
Proceedings of the sixteenth ACM symposium on Operating systems principles
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Information Retrieval
Connections: using context to enhance file search
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
Reducing file system latency using a predictive approach
USTC'94 Proceedings of the USENIX Summer 1994 Technical Conference on USENIX Summer 1994 Technical Conference - Volume 1
Provenance-aware storage systems
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Predicting file system actions from prior events
ATEC '96 Proceedings of the 1996 annual conference on USENIX Annual Technical Conference
Using provenance to aid in personal file search
ATC'07 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference
An extended evaluation of two-phase scheduling methods for animation rendering
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Automatic identification of application I/O signatures from noisy server-side traces
FAST'14 Proceedings of the 12th USENIX conference on File and Storage Technologies
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Storage management activities, such as reporting, file placement, migration and archiving, require the ability to discover files that belong to an application workflow by relying only on information from the file server. Some classes of application workflows, such as rendering an animated sequence from its graphics models or building an application from its source files, often exhibit a high degree of repeatability. We describe a system called Autograph that exploits this repeatability to discover files that belong to an application workflow. Our approach examines traces of file accesses, finds repeated and correlated accesses, and infers which files likely belong to the same workflow. Our solution targets server workflows and uses file server traces, which contain less process and file information than the local machine traces used in prior work. We show that Autograph successfully extracts workflow file signatures, even if the workflows are concurrent or share files.