Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
Solving problems in parallel and distributed computing through the use of bio-inspired techniques. Recent years have seen a surge of interest in computational methods patterned after natural phenomena, with biologically inspired techniques such as fuzzy logic, neural networks, simulated annealing, g...
| Otros Autores: | , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified]
Wiley Interscience Imprint
2000
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755124706719 |
Tabla de Contenidos:
- Distributed cellular automata : large-scale simulation of natural phenomena
- Parallel implementations of evolutionary algorithms
- Towards hybrid biologically inspired heuristics
- Nature-inspired optimization algorithms for parallel simulations
- An introduction to genetic-based scheduling in parallel-processor systems
- Mapping tasks onto distributed heterogenous computing systems using genetic algorithm approach
- Evolving cellular automata-based algorithms for multiprocessor scheduling
- Parallel task mapping with biological computing models
- Scheduling parallel prgrams using genetic algorithms
- Applications of neural networks to mobile communication systems.
