CiC (RDDC): Continuous Bulk Processing in the Cloud

本研究探索了一种替代的数据处理架构，从根本上提高了计算效率，以降低成本，并为云计算提供增强的数据挖掘功能。 IT、医疗和科学信息学的下一个重大进步将主要取决于我们存储、管理和分析大量信息的能力。 对于许多重要的问题，数据采集工具的进步正在迅速提高数据生成速率，超出了我们管理和处理它们产生的数据的能力。该提案研究了用于连续批量数据处理的新架构，该架构支持对连续批次的输入数据执行复杂的多步计算的数据密集型应用程序（例如，从科学或医疗仪器），允许分析简单地更新，而不是重新计算，当新的数据到达。 该研究旨在将增量处理提升为一流的抽象，显著降低数据密集型项目利用云计算的障碍。 为此，这项工作将开发数据分析门户架构，以增加跨各种应用领域的按需数据分析的范围。 作为一个案例研究，它将开发一个针对脂肪肝疾病的门户网站，允许护理人员按需访问医学分析，以改善护理，降低成本，并改善这种重要疾病的临床结果。

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.