SHF: Small: Programming Foundations for Real-Time Data Analysis

SHF：小型：实时数据分析的编程基础

• 批准号: 2008096
• 负责人: Konstantinos Mamouras
• 金额: $ 50万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008096&HistoricalAwards=false
• 关键词: SHF; Small; Programming; Foundations; Real

Modern information-processing systems handle large volumes of data that are produced in real time and need immediate analysis. These real-time data analyses are used to extract insights and enable decision-making in various application domains, such as business intelligence and patient monitoring. Existing systems for processing real-time (streaming) data focus on providing efficient and scalable execution over a distributed computing infrastructure. A common problem with these systems is that their behavior is not clearly specified, which makes it difficult to reason about their correctness. In many cases, the distributed execution of a streaming data analysis gives rise to unpredictable behavior that is not reproducible. The project's novelties are the development of a formal framework for specifying the behavior of real-time data-processing systems and the use of this framework for ensuring the reproducibility of computations. The project's impacts are advances in the practice of programming trustworthy and repeatable streaming data analyses.The project develops a novel programming foundation that encompasses the semantics of data-stream processing, the associated principles of query-language design, and a robust distributed implementation. A denotational semantics is described using a type discipline that captures various notions of data models and data invariants. Basic programming abstractions for stream processing are identified, which enable the modular specification of complex streaming analyses. An implementation is developed that guarantees efficient and reproducible distributed execution. The usefulness of the framework is established with case studies from the domains of enterprise business intelligence and patient monitoring in healthcare.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代信息处理系统处理大量的真实的时间产生的数据，需要立即分析。这些实时数据分析用于提取洞察力，并在各种应用领域（如商业智能和患者监测）中进行决策。用于处理实时（流式）数据的现有系统集中于在分布式计算基础设施上提供高效且可扩展的执行。这些系统的一个常见问题是它们的行为没有明确规定，这使得很难推理它们的正确性。在许多情况下，流数据分析的分布式执行会导致不可重现的不可预测行为。该项目的新颖之处是开发了一个正式的框架，用于指定实时数据处理系统的行为，并使用该框架来确保计算的可重复性。该项目的影响是在编程可信和可重复的流数据analysis.The项目开发了一个新的编程基础，包括数据流处理的语义，查询语言设计的相关原则，和一个强大的分布式实现的实践进步。指称语义描述使用类型的纪律，捕捉各种概念的数据模型和数据不变式。流处理的基本编程抽象的确定，使复杂的流分析的模块化规范。一个实现，保证高效和可再现的分布式执行。该框架的实用性是通过企业商业智能和医疗保健患者监测领域的案例研究建立的。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Compositional Framework for Quantitative Online Monitoring over Continuous-Time Signals

连续时间信号定量在线监测的组合框架

• DOI: 10.1007/978-3-030-88494-9_8
• 发表时间: 2021
• 期刊: Runtime Verification 2021
• 作者: Mamouras, Konstantinos;Chattopadhyay, Agnishom;Wang, Zhifu
• 通讯作者: Wang, Zhifu

Regular Expression Matching using Bit Vector Automata

使用位向量自动机进行正则表达式匹配

• DOI: 10.1145/3586044
• 发表时间: 2023
• 期刊: Proceedings of the ACM on Programming Languages
• 作者: Le Glaunec, Alexis;Kong, Lingkun;Mamouras, Konstantinos
• 通讯作者: Mamouras, Konstantinos

StreamQL: A Query Language for Processing Streaming Time Series

• DOI: 10.1145/3428251
• 发表时间: 2020-11-01
• 期刊: PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL
• 影响因子: 1.8
• 作者: Kong, Lingkun;Mamouras, Konstantinos
• 通讯作者: Mamouras, Konstantinos

PaSh: light-touch data-parallel shell processing

• DOI: 10.1145/3447786.3456228
• 发表时间: 2020-07
• 期刊: Proceedings of the Sixteenth European Conference on Computer Systems
• 作者: N. Vasilakis;Konstantinos Kallas;Konstantinos Mamouras;Achilleas Benetopoulos;Lazar Cvetkovich

Software-Hardware Codesign for Efficient In-Memory Regular Pattern Matching

用于高效内存中正则模式匹配的软硬件协同设计

• DOI: 10.1145/3519939.3523456
• 发表时间: 2022
• 期刊: Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation
• 作者: Kong, Lingkun;Yu, Qixuan;Chattopadhyay, Agnishom;Le Glaunec, Alexis;Huang, Yi;Mamouras, Konstantinos;Yang, Kaiyuan
• 通讯作者: Yang, Kaiyuan