Hybrid Task Scheduling Method for Cloud Computing by Genetic and DE Algorithms
2017
Cloud computing is a new technology which provides online services to the consumers. In order to have a high efficiency in cloud computing, proper task scheduling is required. Since the task scheduling in cloud computing is regarded as an NP complete problem, so traditional heuristic algorithms do not have the required efficiency in this environment. Therefore, recently, the majority of the proposed task scheduling algorithms have focused on hybrid meta-heuristic methods for task scheduling. In this paper, we proposed a hybrid meta-heuristic method by using HEFT algorithm. The obtained results of the simulation and statistical analysis revealed that the proposed algorithm outperforms three other heuristic and genetic algorithms in terms of the makespan in the randomly Direct Acyclic Graphs (DAGs).
Keywords:
- Computer science
- Real-time computing
- Flow shop scheduling
- Fair-share scheduling
- Two-level scheduling
- Fixed-priority pre-emptive scheduling
- Distributed computing
- Dynamic priority scheduling
- Algorithm
- Round-robin scheduling
- Rate-monotonic scheduling
- Genetic algorithm scheduling
- Theoretical computer science
- Job shop scheduling
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