Security-Driven Heuristics and A Fast Genetic Algorithm for Trusted Grid Job Scheduling
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
A taxonomy of Data Grids for distributed data sharing, management, and processing
ACM Computing Surveys (CSUR)
Adjusted fair scheduling and non-linear workload prediction for QoS guarantees in grid computing
Computer Communications
Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems
IEEE Transactions on Parallel and Distributed Systems
Fair Scheduling Algorithms in Grids
IEEE Transactions on Parallel and Distributed Systems
Heuristic solutions to resource allocation in grid computing: a natural approach
The Journal of Supercomputing
Adaptive Divisible Load Model for Scheduling Data-Intensive Grid Applications
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
A2DLT: Divisible Load Balancing Model for Scheduling Communication-Intensive Grid Applications
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Extremal Optimization as a Viable Means for Mapping in Grids
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
New Optimal Load Allocation for Scheduling Divisible Data Grid Applications
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
A multiobjective evolutionary approach for multisite mapping on grids
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Grid scheduling optimization under conditions of uncertainty
NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Multi-round real-time divisible load scheduling for clusters
HiPC'08 Proceedings of the 15th international conference on High performance 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
Optimal workload allocation model for scheduling divisible data grid applications
Future Generation Computer Systems
Time and cost trade-off management for scheduling parallel applications on Utility Grids
Future Generation Computer Systems
Future Generation Computer Systems
Scheduling parallel applications on utility grids: time and cost trade-off management
ACSC '09 Proceedings of the Thirty-Second Australasian Conference on Computer Science - Volume 91
A distributed bio-inspired method for multisite grid mapping
Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
A PTS-PGATS based approach for data-intensive scheduling in data grids
Frontiers of Computer Science in China
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
Performance investigation of weighted meta-scheduling algorithm for scientific grid
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Multiobjective differential evolution for mapping in a grid environment
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
Bacterial foraging based hyper-heuristic for resource scheduling in grid computing
Future Generation Computer Systems
Multidomain hierarchical resource allocation for grid applications
Journal of Electrical and Computer Engineering - Special issue on Resource Allocation in Communications and Computing
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Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as compute resource, networks, storage, and most importantly data collections for large-scale data intensive problems. Because of the massive size and distributed nature of these datasets, scheduling Data Grid applications must consider communication and computation simultaneously to achieve high performance. In many Data Grid applications, Data can be decomposed into multiple independent sub datasets and distributed for parallel execution and analysis. In this paper, we exploit this property and propose a novel Genetic Algorithm based approach that automatically decomposes data onto communication and computation resources. The proposed GA-based scheduler takes advantage of the parallelism of decomposable Data Grid applications to achieve the desired performance level. We evaluate the proposed approach comparing with other algorithms. Simulation results show that the proposed GA-based approach can be a competitive choice for scheduling large Data Grid applications in terms of both scheduling overhead and the relative solution quality as compared to other algorithms.