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Title:A Scalable Self -Diagnosing Content Distribution Service With Bounded Latency
Author(s):Huang, Chengdu
Doctoral Committee Chair(s):Abdelzaher, Tarek F.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Computer Science
Abstract:The self-diagnosing capability of our service comes from the scalable learning-based performance problem diagnosis techniques we propose. The increasing complexity of systems has motivated design of machine learning approaches to automate some system management tasks. However, with increase in scale, current approaches suffer from serious scalability issues. We present two scalable learning-based techniques that automatically identify probable causes of performance problems in large server systems with multiple tiers and replicated sites. By incorporating a large number of diagnostic information sources using a temporal segmentation mechanism and applying transfer learning techniques, we achieve both scalability and improved diagnosis accuracy.
Issue Date:2007
Description:156 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
Other Identifier(s):(MiAaPQ)AAI3290251
Date Available in IDEALS:2015-09-25
Date Deposited:2007

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