CSR---EHS: Collaborative Research: QoS-Aware Data Services in Data-Intensive Real-Time Embedded Applications

CSR---EHS：协作研究：数据密集型实时嵌入式应用中的 QoS 感知数据服务

• 批准号: 0614771
• 负责人: Kyoung-Don Kang
• 金额: $ 24.5万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0614771&HistoricalAwards=false
• 关键词: CSR; EHS; Collaborative; Research; QoS

Timely processing of real-time transactions using fresh temporal data, which reflect the current real world status, is essential in data-intensive real-time embedded applications such as traffic control, agile manufacturing, and defense applications. An overarching goal of this research is developing a novel theoretic framework and prototypical RTEDB (Real-Time Embedded Database) system that can support the desired transaction timeliness and data freshness even in the presence of data/resource contention and dynamic workloads. This project is developing effective Quality of Service (QoS) metrics, novel control theoretic models, feedback control, and feed-forward approaches to specify the desired QoS, model RTEDB dynamics, and support the desired QoS based on the mathematical model, while preventing severe data conflicts. The research is developing several new workload adjustment techniques including adaptive temporal data update, adaptive concurrency control, admission control, and service differentiation techniques to gracefully adapt and differentiate real-time data service with minimal impacts on the user perceived QoS. To improve the scalability of real-time data service, the research focuses on load balancing and temporal data replication in a control area. The research also is developing novel approaches for efficient, secure data transmission in real-time embedded applications. Moreover, the research team is committed to integrating this leading-edge research with teaching and outreach programs. The project, if successful, ultimately envisions that QoS-aware RTEDBs will be used in a number of important data-intensive real-time embedded applications.

使用新的时间数据及时处理实时交易（反映当前现实世界状态），对于数据密集型实时嵌入式应用程序，例如交通控制，敏捷制造和国防应用程序至关重要。这项研究的一个总体目标是开发一种新颖的理论框架和原型RTEDB（实时嵌入式数据库）系统，该系统即使在存在数据/资源竞争和动态工作量的情况下，也可以支持所需的交易时间和数据新鲜度。该项目正在开发有效的服务质量（QoS）指标，新颖的控制理论模型，反馈控制和馈送前进方法，以指定所需的QoS，模型RETTERB动力学，并基于数学模型支持所需的QoS，同时防止严重的数据冲突。该研究正在开发几种新的工作负载调整技术，包括自适应时间数据更新，自适应并发控制，入学控制和服务差异化技术，以优雅地适应和区分实时数据服务，对用户感知的QoS产生最小的影响。为了提高实时数据服务的可扩展性，研究重点是控制区域中的负载平衡和时间数据复制。该研究还正在开发新的方法，以实时嵌入式应用程序中有效，安全的数据传输。此外，研究团队致力于将这项领先的研究与教学和外展计划相结合。如果成功的话，该项目最终会设想QoS感知的RTEDB将用于许多重要的数据密集的实时嵌入式应用程序中。