US Ignite: Collaborative Research: Focus Area 2: Resilient Virtual Path Management for Scalable Data-intensive Computing at Network-Edges

该项目致力于引导和管理托管可视化云计算(VCC)应用程序的虚拟路径网络，以确保灾难事件期间的公共安全。该项目通过以下方式满足事故支持VCC应用程序的需求：(A)对事故现场收集的图像/视频数据进行可扩展处理，以及(B)使用瘦客户端技术进行协作，这些应用程序对于急救人员获得快速视觉态势感知至关重要。还将与急救机构合作进行有针对性的演示，如创伤护理医院(具有战区规模的使用案例)和县消防区(具有区域规模的使用案例)。具体而言，该项目的目标是：(I)研究虚拟路径管理算法和大规模仿真，目的是在主机/链路故障、主机移动性和网络分区的情况下为弹性VCC应用提供有保证的性能；(Ii)在GENI和CloudLab等实验实验台上展示这种路径管理算法在雾-云混合基础设施中的弹性资源配置。本项目的突出理论贡献在于为实时VCC应用设计了新颖的分布式和联邦算法来解决虚拟路径嵌入和计算布局问题。特别是，该项目寻求在存在严重的主机和链路故障、主机移动性和网络分区的情况下，对受限路径寻路器方案的解决方案进行改进，例如，虚拟网络嵌入或流量控制。这项工作还通过允许雾-云计算位置选择权衡的方案，提高了应用感知网络设计的知识。特别是，该方法的基础是在延迟关键型VCC应用的背景下分离视觉数据处理的小/大实例：(A)用于在事件现场的第一响应者和事件指挥官人员协调的“战区规模”，以及(B)用于在来自机载平台的广域运动图像中跟踪不同地理尺度的感兴趣对象的“区域规模”。

This project addresses bootstrapping and managing virtual path networks hosting Visual Cloud Computing (VCC) applications for public safety during disaster incidents. This project meets the needs of incident-supporting VCC applications that are essential for first responders to gain rapid visual situational awareness through: (a) scalable processing of imagery/video data collected at incident scenes, and (b) use of thin-client technologies for collaboration. Targeted demonstrations will also be conducted in collaboration with first-responder agencies such as trauma care hospitals (with theater-scale use cases) and a county fire protection district (with regional-scale use cases). Specifically, the project objectives are to: (i) investigate virtual path management algorithms and large-scale simulations with the aim of providing resilient VCC applications with guaranteed performance even in the presence of host/link failures, host mobility and network partitioning; and (ii) demonstrate resilient resource provisioning for such path management algorithms within hybrid fog-cloud infrastructures on experimental testbeds such as GENI and CloudLab.The salient theoretical contribution of this project lays in the design of novel distributed and federated algorithms for the virtual path embedding and computation placement problems, for real-time VCC applications. In particular, the project seeks a solution improvement for constrained path finders schemes, e.g., virtual network embedding or traffic steering, in presence of severe host and link failures, host mobility and network partitioning. The work also advances knowledge of application-aware network design through a scheme that allows fog-cloud compute location selection tradeoffs. In particular, the approach is based on decoupling small/large instances of visual data processing in the context of latency-critical VCC applications at: (a) "theater-scale" for first-responder and incident commander personnel co-ordination at an incident scene, and (b) "regional-scale" for tracking objects of interest across different geographical scales in wide-area motion imagery from airborne platforms.