CiC (RDDC): Continuous Bulk Processing in the Cloud

CiC (RDDC)：云端连续批量处理

• 批准号: 1048296
• 负责人: Kenneth Yocum
• 金额: $ 36万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1048296&HistoricalAwards=false
• 关键词: CiC; RDDC; Continuous; Bulk; Processing

This research explores an alternative data processing architecture thatfundamentally improves computing efficiency to reduce costs and provideenhanced data mining capabilities for cloud computing. The next majoradvancements in IT, medical, and science informatics will largely bedictated by our ability to store, manage, and analyze large amounts ofinformation. For many important problems, advances in data acquisitiontools are rapidly increasing data generation rates, exceeding our abilityto manage and process the data they produce.This proposal investigates novel architectures for continuous bulk dataprocessing, which support data-intensive applications that perform complexmulti-step computations over successive batches of input data (e.g., fromscientific or medical instruments), allowing analytics to simply beupdated, not recomputed, when new data arrives. The research seeks toraise incremental processing as a first-class abstraction, significantlylowering the barrier of data-intensive projects to take advantage of cloudcomputing. Towards that end, the work will develop data analysis portalarchitectures to increase the reach of on-demand data analytics acrossvarious application domains. As a case study, it will develop a portal forfatty-liver disease, allowing care givers on-demand access to medicalanalytics to improve care, reduce cost, and improve clinical outcomes forthis important disease.

这项研究探讨了一种替代数据处理架构，该体系结构可降低计算效率，以降低成本并提供云计算的数据挖掘功能。 IT，医学和科学信息学的下一个主要内容将在很大程度上归结为我们存储，管理和分析大量信息的能力。 For many important problems, advances in data acquisitiontools are rapidly increasing data generation rates, exceeding our abilityto manage and process the data they produce.This proposal investigates novel architectures for continuous bulk dataprocessing, which support data-intensive applications that perform complexmulti-step computations over successive batches of input data (e.g., fromscientific or medical instruments), allowing analytics to simply beupdated, not重新计算新数据到达时。 该研究将toraise增量处理作为一流的抽象，这显着降低了数据密集型项目的障碍，以利用云计算。 为此，这项工作将开发数据分析门户网站，以增加各种应用程序域的按需数据分析的覆盖范围。 作为一个案例研究，它将开发出肝病的门户，使护理人员按需获得医疗分析的机会改善护理，降低成本并改善临床结果的重要疾病。