CC* Network Design: Improve Network on Campus for Research and Education in Agriculture, Science, and Engineering at Prairie View A&M University

CC* 网络设计：改善 Prairie View A 校园农业、科学和工程研究和教育网络

• 批准号: 1827243
• 负责人: Suxia Cui
• 金额: $ 50万
• 依托单位: Prairie View A & M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827243&HistoricalAwards=false
• 关键词: CC; Network; Design; Improve; Campus

Prairie View A&M University (PVAMU), a Historically Black College and University, is implementing a Science DMZ to Improve Network on Campus for Research and Education in Agriculture, Science, and Engineering (INCREASE), which is an upgrade to current cyberinfrastructure that allows researchers to effectively work in the fields of Big Data and Data Intensive science. This INCREASE project enables data driven research in the areas of cyber security, high performance computing, computational chemistry, brain imaging, genomics, and bioinformatics. It provides better visualization and collaboration mechanisms for PVAMU researchers from seven departments in three colleges. It leads to better educational resources to train students at a minority serving institution. The INCREASE project specifically ties researchers from four research centers closely together to form a new foundation of campus cyberinfrastructure.The INCREASE network, bypassing PVAMU-IT's firewall, integrates with existing infrastructure and provides improved connectivity between PVAMU and Internet2 via Lonestar Education and Research Network (LEARN). It also provides high bandwidth interconnectivity to other research universities and High Performance Computing resources nationwide. As part of the network design, the need for Software Defined Networking solutions that can selectively steer Science DMZ traffic around the campus firewall solution as well as look into implementing a deep-packet inspection and Intrusion Prevention Service to route unregistered connections in and out of the Science DMZ is considered. The study and exploration of the INCREASE network can provide guidance for universities of similar scale to pursue and utilize research resources.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Prairie View A M University（PVAMU）是一所历史悠久的黑人学院和大学，正在实施科学DMZ，以改善农业，科学和工程（INCREASE）的研究和教育校园网络，这是对当前网络基础设施的升级，使研究人员能够有效地在大数据和数据密集型科学领域工作。这个INCREASE项目使网络安全，高性能计算，计算化学，脑成像，基因组学和生物信息学领域的数据驱动研究成为可能。它提供了更好的可视化和协作机制PVAMU研究人员从七个部门在三个学院。它导致更好的教育资源，在少数民族服务机构培训学生。INCREASE项目将来自四个研究中心的研究人员紧密联系在一起，形成校园网络基础设施的新基础。INCREASE网络绕过PVAMU-IT的防火墙，与现有基础设施集成，并通过Lonestar教育和研究网络（LEARN）提供PVAMU与Internet 2之间的更好连接。它还为全国其他研究型大学和高性能计算资源提供高带宽互连。作为网络设计的一部分，需要软件定义网络解决方案，可以选择性地引导科学DMZ流量绕过校园防火墙解决方案，并考虑实施深度数据包检测和入侵防御服务，以路由未注册的连接进出科学DMZ。INCREASE网络的研究和探索可以为类似规模的大学追求和利用研究资源提供指导。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Accelerating AI/ML Workflows with Intelligence Processing Units (IPUs)

使用智能处理单元 (IPU) 加速 AI/ML 工作流程

• 发表时间: 2023
• 期刊: Practice and Experience in Advanced Research Computing (PEARC
• 作者: A. S. Nasari, L. Zhai

Copula Approach for Developing a Biomarker Panel for Prediction of Dengue Hemorrhagic Fever

• DOI: 10.1007/s40745-020-00293-x
• 发表时间: 2020-06
• 期刊: Annals of Data Science
• 作者: Jong-Min Kim;H. Ju;Yoonsung Jung

Enhancing Underwater Image Using Degradation Adaptive Adversarial Network

• DOI: 10.1109/icip46576.2022.9897624
• 发表时间: 2022-10
• 期刊: 2022 IEEE International Conference on Image Processing (ICIP)
• 作者: Lujun Zhai;Yonghui Wang;Suxia Cui;Yu Zhou

Fake Face Detection using Local Binary Pattern and Ensemble Modeling

使用局部二进制模式和集成建模的假脸检测

• DOI: 10.1109/icip42928.2021.9506460
• 发表时间: 2021
• 期刊: IEEE
• 作者: Wang, Yonghui;Zarghami, Vahid;Cui, Suxia
• 通讯作者: Cui, Suxia