Intelligent storage: Cross-layer optimization for soft real-time workload
ACM Transactions on Storage (TOS)
Towards self-predicting systems: What if you could ask ‘what-if’?
The Knowledge Engineering Review
TBBT: scalable and accurate trace replay for file server evaluation
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
A five-year study of file-system metadata
ACM Transactions on Storage (TOS)
Measurement and analysis of large-scale network file system workloads
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Learning and multiagent reasoning for autonomous agents
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Adaptive job routing and scheduling
Engineering Applications of Artificial Intelligence
Discovery of application workloads from network file traces
FAST'10 Proceedings of the 8th USENIX conference on File and storage technologies
Using provenance to extract semantic file attributes
TAPP'10 Proceedings of the 2nd conference on Theory and practice of provenance
Differentiated storage services
ACM SIGOPS Operating Systems Review
Management of Multilevel, Multiclient Cache Hierarchies with Application Hints
ACM Transactions on Computer Systems (TOCS)
Differentiated storage services
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
A cooperation mechanism in agent-based autonomic storage systems
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
ORAID: an intelligent and fault-tolerant object storage device
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Interactive analytical processing in big data systems: a cross-industry study of MapReduce workloads
Proceedings of the VLDB Endowment
SAW: system-assisted wear leveling on the write endurance of NAND flash devices
Proceedings of the 50th Annual Design Automation Conference
Hi-index | 0.00 |
To tune and manage themselves, file and storage systems must understand key properties (e.g., access pattern, lifetime, size) of their various files. This paper describes how systems can automatically learn to classify the properties of files (e.g., read-only access pattern, short-lived, small in size) and predict the properties of new files, as they are created, by exploiting the strong associations between a fileýs properties and the names and attributes assigned to it. These associations exist, strongly but differently, in each of four real NFS environments studied. Decision tree classifiers can automatically identify and model such associations, providing prediction accuracies that often exceed 90%. Such predictions can be used to select storage policies (e.g., disk allocation schemes and replication factors) for individual files. Further, changes in associations can expose information about applications, helping autonomic system components distinguish growth from fundamental change.