Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
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
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
Performance Modeling and Prediction of Nondedicated Network Computing
IEEE Transactions on Computers
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
A Genetic Algorithm Based Approach for Scheduling Decomposable Data Grid Applications
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
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
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
An innovative perspective on mapping in grids
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
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Effective and efficient mapping algorithms for multisite parallel applications are fundamental to exploit the potentials of grid computing. Since the problem of optimally mapping is NP-complete, evolutionary techniques can help to find near-optimal solutions. Here a multiobjective Differential Evolution is investigated to face the mapping problem in a grid environment aiming at reducing the degree of use of the grid resources while, at the same time, maximizing Quality of Service requirements in terms of reliability. The proposed mapper is tested on different scenarios.