Data Mining Systems Using Grid Computing

Distribution of data and computation allows for solving larger problems and execute applications that are distributed in nature. The Grid is a distributed computing infrastructure that enables coordinated resource sharing within dynamic organizations consisting of individuals, institutions, and resources. The Grid extends the distributed and parallel computing paradigms allowing resource negotiation and dynamical allocation, heterogeneity, open protocols and services. Grid environments can be used both for compute intensive tasks and data intensive applications as they offer resources, services, and data access mechanisms. Data mining algorithms and knowledge discovery processes are both compute and data intensive, therefore the Grid can offers a computing and data management infrastructure for supporting decentralized and parallel data analysis. This paper discusses how Grid computing can be used to support distributed data mining. Grid-based data mining uses Grids as decentralized high-performance platforms where to execute data mining tasks and knowledge discovery algorithms and applications. Here we outline some research activities in Grid-based data mining; some challenges in this area and ketch some promising future directions for developing Grid based distributed data mining.