In this paper we present G-Net, a distributed algorithm able to infer classifiers from pre-collected data, and its implementation on Networks of Workstations (NOWs). In order to effectively exploit the computing power provided by NOWs, 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.
High-Performance Data Mining on Networks of Workstations
ANGLANO, Cosimo Filomeno;
1999-01-01
Abstract
In this paper we present G-Net, a distributed algorithm able to infer classifiers from pre-collected data, and its implementation on Networks of Workstations (NOWs). In order to effectively exploit the computing power provided by NOWs, 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.File in questo prodotto:
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