Cost efficient scheduling of big data application workflows on cloud through information correlation

在云上调度的大数据应用程序工作流内部和之间的信息相关性可以通过避免执行许多相关的工作流活动来帮助显着降低整体调度成本。本项目旨在系统地研究这种相关性的成本效益调度。预期成果是：为这一重要的云和大数据研究领域建立基于信息关联的调度研究和实用解决方案;使云上的关键大数据应用领域受益，如医院，保险公司和政府信息服务;并通过创新的行业应用帮助澳大利亚保持在云和大数据研究的前沿。

Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.