CSR: Small: Timely Power-Aware Data Management in Embedded Systems

CSR：小型：嵌入式系统中的及时功耗感知数据管理

• 批准号: 1526932
• 负责人: Kyoung-Don Kang
• 金额: $ 45万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526932&HistoricalAwards=false
• 关键词: CSR; Small; Timely; Power; Aware

In emerging embedded and cyber physical applications like smart cars, micro grids, and homeland security, data amounts are increasing fast. Database support is essential in data-intensive embedded applications, because developing them without database support is hard and error-prone. Ideally, a database system needs to process real-time data service requests, such as driving route recommendations and electricity demand/supply analysis, in a timely manner using fresh data representing the current real-world status, e.g., the present traffic or electric grid status. It is also important the database should consume minimal power considering stringent power constraints in embedded systems. Achieving this vision is challenging for several reasons, including dynamic workloads varying in time depending on the current real world status, severe data/resource contention, and computational costs for updating temporal data. Moreover, the timeliness, data freshness, and power efficiency may compete with each other. If higher priority is given to user queries, their timeliness can be improved at the cost of the decreased data freshness or vice-versa. Simply consuming more power to support the desired timeliness and data freshness is not desirable. Unfortunately, state-of-the-art database systems may fall short of power-aware real-time data services. Non-real-time databases unaware of timing and data freshness requirements may perform poorly in these applications. Most existing real-time and embedded databases can provide no guarantee on the desired timeliness and data freshness. Neither are they power-aware. This can be a serious problem, since the unbounded tardiness or data staleness may result in a traffic jam, power outage, or homeland security problem. Although research on energy-efficient databases mainly in data center contexts has recently begun, real-time deadlines and data freshness requirements are not considered. Despite the importance, related work on power management in real-time databases, chiefly targeting embedded applications, is surprisingly scarce. Due to the power ignorance, deploying real-time databases may become increasingly difficult and costly. To bridge the gap, in-depth research will be performed in this work to investigate effective fundamental approaches for power-aware real-time data services in emerging embedded and cyber physical systems with significant broader impacts. This project will investigate novel methods to support the desired timeliness and data freshness even in the presence of dynamic workloads, while substantially decreasing the power consumption in real-time embedded databases (RTEDBs). This will involve exploring 1) application of adaptive control theoretic techniques to gracefully adapt the RTEDB system behavior, if necessary, to support the desired timeliness and data freshness for less power in the closed-loop system; 2) feedforward methods to avoid data/resource contention incurring performance and power penalties by considering RTEDB semantics; 3) a multicore RTEDB system architecture, in which the cores support the desired timeliness and data freshness, decreasing the power usage both autonomously and collaboratively; and 4) extensive simulations and experiments in a testbed will be performed using real-world data traces to measure the timeliness, data freshness, and power and energy consumption.

在新兴的嵌入式和网络物理应用中，例如智能汽车，微电网和国土安全性，数据量正在迅速增加。数据库支持在数据密集型嵌入式应用程序中至关重要，因为在没有数据库支持的情况下开发它们是艰难且容易出错的。理想情况下，数据库系统需要及时处理实时数据服务请求，例如驾驶路线建议和电力需求/供应分析，使用代表当前现实世界状态的新数据，例如当前的流量或电网状态。考虑到嵌入式系统中严格的功率约束，数据库应消耗最小的功率。实现这一愿景的原因有几个原因，包括及时的动态工作负载，具体取决于当前的现实世界状况，严重的数据/资源争夺以及更新时间数据的计算成本。此外，及时性，数据新鲜度和功率效率可能会相互竞争。如果对用户查询的优先级更高，则可以以降低数据新鲜度或反之亦然来提高其及时性。仅需消耗更多的能力来支持所需的及时性和数据新鲜度。不幸的是，最先进的数据库系统可能缺乏电力感知的实时数据服务。在这些应用程序中，非实时时间数据库不知道时间和数据新鲜度要求的性能很差。大多数现有的实时和嵌入式数据库都无法提供有关所需的及时性和数据新鲜度的保证。他们也不是能力意识。这可能是一个严重的问题，因为无界的拖延或数据陈旧可能会导致交通拥堵，停电或国土安全问题。尽管最近对数据中心环境中的节能数据库进行的研究最近已经开始，但未考虑实时截止日期和数据新鲜度要求。尽管很重要，但在实时数据库中的电源管理方面的相关工作（主要针对嵌入式应用程序）令人惊讶地稀缺。由于无知，部署实时数据库可能会变得越来越困难和昂贵。为了弥合差距，将在这项工作中进行深入的研究，以调查具有更广泛影响的新兴嵌入式和网络物理系统中的有效的实时数据服务的有效基本方法。该项目将研究新的方法，即使在存在动态工作量的情况下，也将支持所需的及时性和数据新鲜度，同时大大降低了实时嵌入式数据库（RTEDBS）中的功耗。 这将涉及探索1）应用自适应控制理论技术，以优雅地适应RTEDB系统行为，如有必要，以支持所需的及时性和数据新鲜度，以减少闭环系统中的功率； 2）通过考虑RETTERB语义，避免数据/资源竞争的方法/资源竞争的方法； 3）多核心RTEDB系统体系结构，其中核心支持所需的及时性和数据新鲜度，从而自主和协作降低功率使用； 4）将使用现实世界数据跟踪进行测试床中的大量模拟和实验，以测量及时性，数据新鲜度以及功率和能量消耗。