High-Performance Data Mining on Networks of Workstations

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