CC*DNI Integration: Network Cyberinfrastructure (CI) for Biomedical Informatics Innovation

大规模网络基础设施应用于生物信息学等应用，导致需要传输和存储大量数据。由于生物医学数据和健康信息系统的大规模和分布式特性，开发健壮、分布式和可扩展的网络基础设施是生物医学信息学研究创新的主要焦点。与这种基础设施相关的问题之一是时间或延迟敏感数据的传输，这通常被描述为服务质量(Qos)。软件定义网络(SDN)技术具有提供服务质量的潜力，但尚未在端到端系统中得到集成和演示。除了医疗保健应用，提供服务质量的集成系统还适用于实时仪器控制、实时视频传输和其他时间敏感应用。该项目正在通过智能中间件服务增强当前的网络基础设施，该服务作为SDN控制器和最终用户应用程序之间的中介运行。灵活的协同调度中间件引擎(称为Flexware)将提供动态配置网络的能力，以最好地支持生物医学输入的各种性质。Flexware结合了几种新兴的智能网络服务，如选播、多播、可生存性和并行传输，用于在共享保护伞下进行大规模生物医学数据存储和检索，从而提供具有定制和优化网络性能的应用程序。该项目将对提高医疗保健应用程序的质量产生重大影响，为临床和科学研究人员提供灵活高效的网络资源分配，以研究患者行为，并培训医疗和工程领域的下一代劳动力。

The application of large-scale cyberinfrastructure to applications such as bio-informatics is resulting in the need to transport and store large quantities of data. Due to the large scale and distributed nature of the biomedical data and health information systems, developing a robust, distributed, and scalable network cyberinfrastructure is a major focus for biomedical informatics research innovation. Among the issues associated with such an infrastructure is the transport of time or delay sensitive data, what is often described as Quality of Service (QoS). Software Defined Network (SDN) technology has the potential for providing QoS but it has not been integrated and demonstrated in end-to-end systems. In addition to health care applications, an integrated system providing QoS is applicable to real time instrument control, transport of real time video and other time-sensitive applications. This project is enhancing the current network infrastructure with an intelligent middleware service that operates as a broker between the SDN controller and the end-user application. The flexible co-scheduling middleware engine (referred to as Flexware) will provide the capability to dynamically configure a network to best support the varied nature of biomedical inputs. Flexware combines several emerging intelligent network services, such as anycast, manycast, survivability, and parallel transfers for large-scale biomedical data storage and retrieval under a shared umbrella that provides an application with customized and optimized network performance. This project will have significant impacts on improving the quality of healthcare applications, providing clinical and scientific researchers with flexible and efficient network resource allocation for studying patient behavior, and training the next generation workforce in medical and engineering fields.