Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Distributed data mining on the grid
Future Generation Computer Systems - Grid computing: Towards a new computing infrastructure
Dynamic, Competitive Scheduling of Multiple DAGs in a Distributed Heterogeneous Environment
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Supporting the optimisation of distributed data mining by predicting application run times
Enterprise information systems IV
MAGE: An Agent-Oriented Programming Environment
ICCI '04 Proceedings of the Third IEEE International Conference on Cognitive Informatics
Web Services Composition for Distributed Data Mining
ICPPW '05 Proceedings of the 2005 International Conference on Parallel Processing Workshops
Weka4WS: a WSRF-enabled weka toolkit for distributed data mining on grids
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Distributed data mining on grids: services, tools, and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A parallel method for large sparse generalized eigenvalue problems using a GridRPC system
Future Generation Computer Systems
Towards a general model of the multi-criteria workflow scheduling on the grid
Future Generation Computer Systems
Editorial: Special section on workflow systems and applications in e-Science
Future Generation Computer Systems
A grid portal for solving geoscience problems using distributed knowledge discovery services
Future Generation Computer Systems
Group-based self-organization grid architecture
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
APHID: An architecture for private, high-performance integrated data mining
Future Generation Computer Systems
Journal of Grid Computing
An empirical study on mining sequential patterns in a grid computing environment
Expert Systems with Applications: An International Journal
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The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an effective scheduling framework. DDM often shares the computing paradigm of local processing and global synthesizing. It involves every phase of Data Mining (DM) processes, which makes the workflow of DDM very complex and can be modelled only by a Directed Acyclic Graph (DAG) with multiple data entries. Motivated by the need for a practical solution of the Grid scheduling problem for the DDM workflow, this paper proposes a novel two-phase scheduling framework, including External Scheduling and Internal Scheduling, on a two-level Grid architecture (InterGrid, IntraGrid). Currently a DM IntraGrid, named DMGCE (Data Mining Grid Computing Environment), has been developed with a dynamic scheduling framework for competitive DAGs in a heterogeneous computing environment. This system is implemented in an established Multi-Agent System (MAS) environment, in which the reuse of existing DM algorithms is achieved by encapsulating them into agents. Practical classification problems from oil well logging analysis are used to measure the system performance. The detailed experiment procedure and result analysis are also discussed in this paper.