ATTRIBUTE-BASED LEARNING ENVIRONMENTS (ABLE) [ Extended Overview | People
| Publications ] Models, created from file attributes, are used to classify the properties
of existing files and Overview To tune and manage themselves, file and storage systems must understand
key properties (e.g., access pattern, lifetime, popularity) of their
files. ABLE allows systems to learn how to automatically classify files
and predict the properties of new files, as they are created, by exploiting
the strong associations between a file's properties and the names and
attributes assigned to it. Such predictions can be used to select policies
(e.g., disk allocation schemes and replication factors) for individual
files. Further, changes in associations can expose information about
applications, helping self-* system components distinguish growth from
fundamental change. PeopleFACULTY STUDENTS Publications
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