Service-Oriented Middleware for Distributed Data Mining on the Grid

Distribution of data and computation allows for solving larger problems and executing 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 for resource negotiation and dynamical allocation, heterogeneity, open protocols, and services. Grid environments can be used both for compute-intensive tasks and data intensive applications by exploiting their resources, services, and data access mechanisms. Data mining algorithms and knowledge discovery processes are both compute and data intensive, therefore the grid can offer 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. Research activities in grid-based data mining and some challenges in this area are presented along with some promising future directions for developing grid-based distributed data mining. (c) 2007 Elsevier Inc. All rights reserved.