CPS: Small: Programming Environment and Architecture for Situational Awareness and Response

CPS：小号：编程环境和体系结构的态势感知和响应本研究的目的是调查和实施的软件体系结构，以提高生产力的快速部署，强大的，实时的态势感知和响应应用程序的开发。该方法是基于一个模块化的跨层架构，结合了以数据为中心的描述性编程模型与基于覆盖的通信模型。跨层架构将促进有效的实施。同时，以数据为中心的编程模型和基于覆盖的通信模型将促进一个健壮的实现，可以利用异构资源和响应不同的故障。目前还没有一个高层次的软件架构，以满足许多态势感知和响应应用程序的严格要求。拟议的项目将通过开发一种新的以数据为中心的编程模型来填补这一空白，该模型跨越具有不同计算和通信能力的设备。类似地，覆盖通信模型将通过将网络资源与编程模型集成来扩展现有工作。这种跨层设计将促进高效和健壮的应用程序的实现。这项研究将通过为紧急救援人员提供及时提供关键信息的软件工具来造福社会。这反过来又会增加安全，减少紧急情况下的经济和人员损失。部署传感器和移动的设备的生产率提高将使其他领域受益，例如使用传感器网络的实地研究。软件将在开源许可证下发布，以促进政府机构，研究机构和个人的使用。这项研究的产品，包括软件，将用于北卡罗来纳州大学的课程。

CPS: Small: Programming Environment and Architecture for Situational Awareness and ResponseThe objective of this research is to investigate and implement a software architecture to improve productivity in the development of rapidly deployable, robust, real-time situational awareness and response applications. The approach is based on a modular cross-layered architecture that combines a data-centric descriptive programming model with an overlay-based communication model. The cross-layer architecture will promote an efficient implementation. Simultaneously, the data-centric programming model and overlay-based communication model will promote a robust implementation that can take advantage of heterogeneous resources and respond to different failures.There is currently no high-level software architecture that meets the stringent requirements of many situational awareness and response applications. The proposed project will fill this void by developing a novel data-centric programming model that spans devices with varying computational and communication capabilities. Similarly, the overlay communication model will extend existing work by integrating network resources with the programming model. This cross-layer design will promote the implementation of efficient and robust applications. This research will benefit society by providing emergency responders with software tools that present key information in a timely fashion. This, in turn, will increase safety and reduce economic and human loss during emergencies. The productivity gains in deploying sensors and mobile devices will benefit other domains, such as field research using sensor networks. Software will be released under an open-source license to promote the use by government agencies, research institutions, and individuals. Products of this research, including the software, will be used in courses at the Universityof North Carolina.