Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Optimal selection theory for superconcurrency
Proceedings of the 1989 ACM/IEEE conference on Supercomputing
Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Efficient scheduling of arbitrary task graphs to multiprocessors using a parallel genetic algorithm
Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
The grid
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Journal of the ACM (JACM)
Future Generation Computer Systems - Special issue on metacomputing
Journal of Parallel and Distributed Computing
MPI-The Complete Reference, Volume 1: The MPI Core
MPI-The Complete Reference, Volume 1: The MPI Core
Journal of Global Optimization
Performance Modeling and Prediction of Nondedicated Network Computing
IEEE Transactions on Computers
MPI_Connect Managing Heterogeneous MPI Applications Ineroperation and Process Control
Proceedings of the 5th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Programming environments for high-performance grid computing: the Albatross project
Future Generation Computer Systems - Grid computing: Towards a new computing infrastructure
Master/Slave Computing on the Grid
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A Directory Service for Configuring High-Performance Distributed Computations
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Grid Information Services for Distributed Resource Sharing
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
Ten actions when Grid scheduling: the user as a Grid scheduler
Grid resource management
A Genetic Algorithm Based Approach for Scheduling Decomposable Data Grid Applications
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
MARS: A Metascheduler for Distributed Resources in Campus Grids
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
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
Quality of Service on the Grid Via Metascheduling with Resource Co-Scheduling and Co-Reservation
International Journal of High Performance Computing Applications
Differential evolution using a neighborhood-based mutation operator
IEEE Transactions on Evolutionary Computation
An economy-driven mapping heuristic for hierarchical master-slave applications in grid systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
EuroPVM/MPI'06 Proceedings of the 13th European PVM/MPI User's Group conference on Recent advances in parallel virtual machine and message passing interface
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Mapping cooperating GRID applications by affinity for resource characteristics
AIS'04 Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems
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Computational grids assemble multisite and multiowner resources and represent the most promising solutions for processing distributed computationally intensive applications, each composed by a collection of communicating tasks. The execution of an application on a grid presumes three successive steps: the localization of the available resources together with their characteristics and status; the mapping which selects the resources that, during the estimated running time, better support this execution and, at last, the scheduling of the tasks. These operations are very difficult both because the availability and workload of grid resources change dynamically and because, in many cases, multisite mapping must be adopted to exploit all the possible benefits. As the mapping problem in parallel systems, already known as NP-complete, becomes even harder in distributed heterogeneous environments as in grids, evolutionary techniques can be adopted to find near-optimal solutions. In this paper an effective and efficient multisite mapping, based on a distributed Differential Evolution algorithm, is proposed. The aim is to minimize the time required to complete the execution of the application, selecting from among all the potential ones the solution which reduces the use of the grid resources. The proposed mapper is tested on different scenarios.