DC: Small: A Programming Model for Distributed Data Fusion

DC：小型：分布式数据融合的编程模型

• 批准号: 1018544
• 负责人: Santosh Pande
• 金额: $ 38万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1018544&HistoricalAwards=false
• 关键词: DC; Small; Programming; Model; Distributed

Data is being generated everywhere in real-time since the scope of sensors has extended to smartphones that continually capture and/or transmit a varied type of data. A lot of data comes in different semantic forms that needs to be distinguished. For example, tweets and instant messages carry different types of information although both are based on text. Such distributed data carries rich semantics that need to be captured and processed for determining the state of the information in near real time and this poses many challenges. This work proposes a language-based (Java) approach along with a mobile agent based system to capture important properties such as timeliness, currency, incompleteness, consistency, and autonomy of data utilizing the properties of their sources. Moreover, since the data sources are quite autonomous, information flow policies dictate access control of the non-local data. Policies pose constraints on data access and movement and multiple processing possibilities exist in such a scenario. Performing such data fusion in real-time is very challenging and it is envisioned to use Java mobile agents framework. The role of compiler analysis is critical to make the runtime smart to reduce undue overhead to get distributed real time processing needs under control. It is proposed to test this software infrastructure on several applications from the domains such as the transportation, and the navigation systems.

由于传感器的范围已经扩展到不断捕获和/或传输各种类型数据的智能手机，因此无处不在地实时生成数据。许多数据以不同的语义形式出现，需要加以区分。例如，tweet和即时消息携带不同类型的信息，尽管它们都基于文本。这种分布式数据包含丰富的语义，需要捕获和处理以近乎实时地确定信息的状态，这带来了许多挑战。这项工作提出了一种基于语言（Java）的方法，以及一个基于移动代理的系统，以捕获重要的属性，如利用数据源的属性的数据的及时性、时效性、不完整性、一致性和自主性。此外，由于数据源是非常自治的，信息流策略规定了对非本地数据的访问控制。策略对数据访问和移动构成约束，并且在这种场景中存在多种处理可能性。实时执行这样的数据融合是非常具有挑战性的，并且设想使用Java移动代理框架。编译器分析的作用对于使运行时智能化以减少不必要的开销以控制分布式实时处理需求至关重要。提出了在交通运输和导航系统等领域的应用中对该软件基础结构进行测试。