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	<pub:MastersThesis rdf:about="http://ebiquity.umbc.edu/paper/html/id/275/A-Mass-Storage-System-Administrator-Autonomic-Assistant">
		<rdfs:label><![CDATA[A Mass Storage System Administrator Autonomic Assistant]]></rdfs:label>
		<pub:title><![CDATA[A Mass Storage System Administrator Autonomic Assistant]]></pub:title>
		<pub:publishedOn rdf:datatype="&xsd;dateTime">2005-12-02T00:00:00-05:00</pub:publishedOn>
		<pub:abstract><![CDATA[The growing complexity of mass storage systems at major data centers
is causing stress on system administrators to keep performance at
optimal levels. As storage requirements grow, so does the number of
routine tasks that the administrator must perform, as well as the time
it takes for these to be executed. The solution being proposed to ease
this burden is the Mass Storage System Administrator Autonomic
Assistant (MSSAAA). The MSSAAA is a collection of agents that perform
some of the more common tasks while the administrators handle
higher-level issues. Using the principles of autonomic computing, the
MSSAAA is governed by a centralized set of policies that the
administrator will review on a regular basis and can adjust as
necessary.  

<p>

The goal is to develop an autonomic assistant to
substantially reduce the amount of time it takes to address specific
problems in the system. Using tools such as IBM]]></pub:abstract>
		<pub:organization><![CDATA[Computer Science and Electrical Engineering]]></pub:organization>
		<pub:counter>3294</pub:counter>
		<pub:publisher><![CDATA[University of Maryland, Baltimore County]]></pub:publisher>
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					<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Randy/Schauer"><person:name><![CDATA[Randy Schauer]]></person:name><rdfs:label><![CDATA[Randy Schauer]]></rdfs:label></person:Person>
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