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

US Ignite：协作研究：重点领域 2：网络边缘可扩展数据密集型计算的弹性虚拟路径管理

• 批准号: 1647084
• 负责人: Flavio Esposito
• 金额: $ 20.38万
• 依托单位: Saint Louis University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1647084&HistoricalAwards=false
• 关键词: US; Ignite; Collaborative; Research; Focus

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.

该项目旨在引导和管理虚拟路径网络托管可视化云计算（VCC）应用程序，以确保灾难事件期间的公共安全。 该项目满足了事故支持VCC应用程序的需求，这些应用程序对于第一响应者获得快速视觉态势感知至关重要：（a）对在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。还将与创伤护理医院（具有剧院规模的用例）和县消防区（具有区域规模的用例）等急救机构合作进行有针对性的演示。 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模拟，目的是即使在主机/链路故障、主机移动性和网络分区的情况下，也能为弹性VCC应用提供有保证的性能;以及（ii）证明在混合雾中用于这种路径管理算法的弹性资源供应。云基础设施的实验测试平台，如GENI和CloudLab。该项目的显着理论贡献在于虚拟路径嵌入和计算布局问题的新的分布式和联邦算法的设计，实时VCC应用程序。特别是，该项目寻求一个解决方案的改进，为约束路径寻找计划，例如，虚拟网络嵌入或流量导向，在存在严重主机和链路故障、主机移动性和网络分区的情况下。这项工作还通过一个允许雾云计算位置选择权衡的方案来推进应用感知网络设计的知识。特别是，该方法是基于解耦的小/大的情况下的视觉数据处理的延迟关键的VCC应用程序：（a）“剧院规模”的第一响应者和事件指挥人员协调在事故现场，和（B）“区域规模”的跟踪对象的兴趣跨越不同的地理尺度在广域运动图像从机载平台。

项目成果

ADELE: An Architecture for Steering Traffic and Computations via Deep Learning in Challenged Edge Networks

ADELE：在面临挑战的边缘网络中通过深度学习引导流量和计算的架构

• DOI: 10.1109/cccs.2019.8888120
• 发表时间: 2019
• 期刊: Communications and Security (ICCCS
• 作者: Gaballo, Alessandro;Flocco, Matteo;Esposito, Flavio;Marchetto, Guido
• 通讯作者: Marchetto, Guido

Catena: A distributed architecture for robust service function chain instantiation with guarantees

Catena：一种具有保证的稳健服务功能链实例化的分布式架构

• DOI: 10.1109/netsoft.2017.8004103
• 发表时间: 2017
• 期刊: IEEE Conference on Network Softwarization (NetSoft
• 作者: Esposito, Flavio

Sustainable Task Offloading in UAV Networks via Multi-Agent Reinforcement Learning

• DOI: 10.1109/tvt.2021.3074304
• 发表时间: 2021-05-01
• 期刊: IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
• 影响因子: 6.8
• 作者: Sacco, Alessio;Esposito, Flavio;Montuschi, Paolo
• 通讯作者: Montuschi, Paolo

Reunifying Families after a Disaster via Serverless Computing and Raspberry Pis

通过无服务器计算和 Raspberry Pi 帮助灾后家庭团聚

• DOI: 10.1109/lanman.2018.8475098
• 发表时间: 2018
• 期刊: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN
• 作者: Franz, Justin;Nagasuri, Tanmayi;Wartman, Andrew;Ventrella, Agnese V.;Esposito, Flavio
• 通讯作者: Esposito, Flavio

Complete edge function onloading for effective backend-driven cyber foraging

• DOI: 10.1109/wimob.2017.8115808
• 发表时间: 2017-10
• 期刊: 2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
• 作者: Flavio Esposito;Andrej Cvetkovski;T. Dargahi;Jianli Pan