A task scheduling algorithm for heterogeneous systems using ACO
2013
A major challenge in task scheduling is the availability of resources. In a heterogeneous environment, where processors operate at different speeds and are not continuously available for computation, achieving a better make-span is a key issue. Our proposed approach try to further optimize this scheduling strategy by using Ant Colony Optimization. We have compared our results with other popular scheduling algorithms such as SSAC and MINMIN. Our results indicate that our proposed technique using Ant Colony Optimization is clearly a better solution for reducing the make-span considerably.
Keywords:
- Scheduling (production processes)
- Nurse scheduling problem
- Real-time computing
- Fair-share scheduling
- Two-level scheduling
- Flow shop scheduling
- Rate-monotonic scheduling
- Distributed computing
- Computer science
- Fixed-priority pre-emptive scheduling
- Dynamic priority scheduling
- Metaheuristic
- Ant colony optimization algorithms
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