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...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
John Wiley,
©2001.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- 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.