An Interactive Resource-Aware Framework for Distributed Data Mining

The computationally-intensive nature of many data mining algorithms and the size of the datasets involved has motivated efforts to use parallel computing to produce timely results. A particularly cost effective computing platform for such parallelizations is a network of workstations (NOW). However, there are many problems associated with efficient parallelizations on a NOW, including data transmission over a low bandwidth network, load-balancing, fault-tolerance, interactivity, programming...