A taxonomy of Data Grids for distributed data sharing, management, and processing
ACM Computing Surveys (CSUR)
A resource broker with an efficient network information model on grid environments
The Journal of Supercomputing
Security-driven scheduling for data-intensive applications on grids
Cluster Computing
Journal of Parallel and Distributed Computing
An adaptive meta-scheduler for data-intensive applications
International Journal of Grid and Utility Computing
Cooperative caching for grid-enabled OLAP
International Journal of Grid and Utility Computing
The Journal of Supercomputing
A general distributed scalable grid scheduler for independent tasks
Journal of Parallel and Distributed Computing
Research on the Trust-Adaptive Scheduling for Data-Intensive Applications on Data Grids
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
A grid resource broker with network bandwidth-aware job scheduling for computational grids
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
A general distributed scalable peer to peer scheduler for mixed tasks in grids
HiPC'07 Proceedings of the 14th international conference on High performance computing
A multi-site resource allocation strategy in computational grids
GPC'08 Proceedings of the 3rd international conference on Advances in grid and pervasive computing
An integrated approach for scheduling divisible load on large scale data grids
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers
The Journal of Supercomputing
File replication, maintenance, and consistency management services in data grids
The Journal of Supercomputing
Design of file size and type of access based replication algorithm for data grid
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Heuristic-based scheduling to maximize throughput of data-intensive grid applications
IWDC'04 Proceedings of the 6th international conference on Distributed Computing
A deadline and budget constrained scheduling algorithm for escience applications on data grids
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
A general data grid: framework and implementation
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
A joint data and computation scheduling algorithm for the grid
Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing
Computers and Operations Research
Hopfield neural network for simultaneous job scheduling and data replication in grids
Future Generation Computer Systems
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Grid computing is moving into two ways. TheComputational Grid focuses on reducing execution timeof applications that require a great number of computerprocessing cycles. The Data Grid provides the way tosolve large scale data management problems. Dataintensive applications such as High Energy Physics andBioinformatics require both Computational and DataGrid features. Job scheduling in Grid has been mostlydiscussed from the perspective of computational Grid.However, scheduling on Data Grid is just a recent focusof Grid computing activities. In Data Grid environment,effective scheduling mechanism considering bothcomputational and data storage resources must beprovided for large scale data intensive applications.In this paper, we describe new scheduling model thatconsiders both amount of computational resources anddata availability in Data Grid environment. Weimplemented a scheduler, called Chameleon, based onthe proposed application scheduling model. Chameleonshows performance improvements in data intensiveapplications that require both large number ofprocessors and data replication mechanisms. Theresults achieved from Chameleon are presented.