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云计算和大数据环境下工作流数据感知调度

Workflow Data Awareness Scheduling under Cloud Computing and Big Data Environments

  • 摘要: 为了解决具有数据约束的工作流多标优化调度问题,提出了一种在保证业务逻辑前提下并考虑数据约束的数据感知调度算法.首先通过将工作流调度建模为一个多目标优化问题,开发了一种数据感知蚁群算法(DACO)来搜索最优调度方式,其次在该算法中将判断每个任务所需的数据量和任务之间的数据约束,感知每个业务之间的数据流,最后分治策略来搜索最优调度.实验结果表明,该算法在效率和成本效益方面优于现有的求解方法.

     

    Abstract: In the report, in order to solve the multi-criteria optimal scheduling problem of workflow with data constraints, a data-aware scheduling algorithm based on business logic and considering data constraints was proposed. Workflow scheduling was modeled as a multi-objective optimization problem, a data-aware ant colony algorithm (DACO) was developed to search the optimal scheduling method, the amount of data required for each task and the data constraints between tasks were determined, the data flow between each business was perceived, and then, the divide-and-conquer strategy to search the optimal scheduling. The results showed that the algorithm is superior to the existing methods in terms of efficiency and cost-effectiveness.

     

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