Nature inspired meta-heuristics for grid scheduling: single and multi-objective optimization approaches
In this chapter, we review a few important concepts from Grid computing related to scheduling problems and their resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the heart of any Grid-like computational system. Different types of scheduling based on different crit...
| Autores: | , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/128951 |
| Acceso en línea: | https://hdl.handle.net/2117/128951 https://dx.doi.org/10.1007/978-3-540-69277-5 |
| Access Level: | acceso abierto |
| Palabra clave: | Computational grids (Computer systems) Computer algorithms Nature inspired meta-heuristics Multi-objective optimization Job scheduling Genetic algorithms Simulated annealing Ant colony Particle swarm optimization Algorismes computacionals Computació distribuïda Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures distribuïdes |
| Sumario: | In this chapter, we review a few important concepts from Grid computing related to scheduling problems and their resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the heart of any Grid-like computational system. Different types of scheduling based on different criteria, such as static vs. dynamic environment, multi-objectivity, adaptivity, etc., are identified. Then, heuristics and meta-heuristics methods for scheduling in Grids are presented. The chapter reveals the complexity of the scheduling problem in Computational Grids when compared to scheduling in classical parallel and distributed systems and shows the usefulness of heuristics and meta-heuristics approaches for the design of efficient Grid schedulers. |
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