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

通过信息关联在云上进行大数据应用工作流的经济高效调度

• 批准号: LP140100816
• 负责人: Prof Jinjun Chen
• 金额: $ 21.15万
• 依托单位: Swinburne University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-03-27 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP140100816
• 关键词: Cost; efficient; scheduling; big; data

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.

在云上调度的大数据应用程序工作流内部和之间的信息关联可以通过避免执行许多相关工作流活动来帮助显着降低总体调度成本。本项目旨在系统地研究成本效益调度的这种相关性。预期成果是：针对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；惠及医院、保险公司、政府信息服务等云上重点大数据应用领域；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。