Inhambu: Data Mining Using Idle Cycles in Clusters of PCs

In this paper we present and evaluate Inhambu, a distributed object-oriented system that relies on dynamic monitoring to collect information about the availability of computational resources, providing the necessary support for the execution of data mining applications on clusters of PCs and workstations. We also describe a modified implementation of the data mining tool Weka, which executes the cross validation procedure in parallel with the support of Inhambu. We present preliminary tests, showing that performance gains can be obtained for computationally expensive data mining algorithms, even when running with small datasets.