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1999
IEEE

High-Performance Knowledge Extraction from Data on PC-Based Networks of Workstations

9 years 6 months ago
High-Performance Knowledge Extraction from Data on PC-Based Networks of Workstations
The automatic construction of classi ers programs able to correctly classify data collected from the real world is one of the major problems in pattern recognition and in a wide area related to Arti cial Intelligence, including Data Mining. In this paper we present G-Net, a distributed algorithm able to infer classi ers from pre-collected data, and its implementation on PC-based Networks of Workstations PC-NOWs. In order to e ectively exploit the computing power provided by PCNOWs, G-Net incorporates a set of dynamic load distribution techniques that allow it to adapt its behavior to variations in the computing power due to resource contention. Moreover, it is provided with a fault tolerance scheme that enables it to continue its computation even if the majority of the machines become unavailable during its execution.
Cosimo Anglano, Attilio Giordana, Giuseppe Lo Bell
Added 03 Aug 2010
Updated 03 Aug 2010
Type Conference
Year 1999
Where IPPS
Authors Cosimo Anglano, Attilio Giordana, Giuseppe Lo Bello
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