CC* Integration: End-to-End Performance and Security Driven Federated Data-Intensive Workflow Management

CC* 集成：端到端性能和安全驱动的联合数据密集型工作流管理

• 批准号: 1827177
• 负责人: Prasad Calyam
• 金额: $ 50万
• 依托单位: University of Missouri-Columbia
• 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: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827177&HistoricalAwards=false
• 关键词: CC; Integration; End; Performance; Security

Data-intensive science applications in research fields such as bioinformatics, chemistry,and material science are increasingly becoming multi-domain in nature. To augment localcampus CyberInfrastructure (CI) resources, these applications rely on multi-institutional resourcesthat are remotely accessible (e.g., scientific instruments, supercomputers, public clouds).Provisioning of such federated CI resources has been traditionally based on applications'performance and quality of service (QoS) requirements. This project aims to augmenttraditional resource provisioning schemes through novel schemes forformalizing end-to-end security requirements to align security postureacross multi-domain resources with heterogeneous policies.This project addresses the end-to-end multi-domain security design forscientific applications by defining and formalizing security specifications along an application's workflow lifecycle stages.The research work will advance the current knowledge for a CI engineer in the following areas:(i) how to intelligently perform resource allocations among private and public cloud locations;(ii) by streamlining end-to-end security posture across domains that are constructed via dynamic network services; and(iii) how to "bring your own compute" programs in large facilities to reduce turnaround times in a secured and policy-compliant manner.The resulting security formalization and alignment schemes will be implemented as a security middleware coupled within a unified resource broker framework that: (a) operationally integrates various software tools and systems such as perfSONAR, OpenStack, iRODS and Shibboleth; and (b) supports prototypes of web-portals and actual users (e.g., researchers and educators) within usability evaluation and validation experiments.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.

生物信息学、化学和材料科学等研究领域的数据密集型科学应用在本质上越来越多地成为多领域。为了增加本地校园网络基础设施（CI）资源，这些应用程序依赖于可远程访问的多机构资源（例如，这种联合CI资源的供应传统上基于应用的性能和服务质量（QoS）要求。该项目旨在通过新的方案来增强传统的资源提供方案，以正式化端到端的安全需求，从而使跨多域资源的安全状态与异构策略保持一致。领域安全设计科学应用程序通过定义和形式化的安全规范沿着应用程序的工作流程生命周期阶段。研究工作将推进现有的知识，CI工程师在以下领域：（i）如何在私有云和公共云位置之间智能地执行资源分配;（ii）通过简化通过动态网络服务构建的域的端到端安全态势;以及（iii）如何在大型设施中“自带计算机”程序，以在安全和政策-所得到的安全形式化和对齐方案将被实现为耦合在统一资源代理框架内的安全中间件，该统一资源代理框架：（a）在操作上整合各种软件工具和系统，如perfSONAR、OpenStack、iRODS和Shibboleth;以及（B）支持门户网站和实际用户的原型（例如，该奖项反映了NSF的法定使命，并被认为值得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来支持。

项目成果

The Winding Road of Requesting Healthcare Data for Analytics Purposes: Using the One-Interview Mental Model Method for Improving Services of Health Data Governance and Big Data Request Processes

出于分析目的请求医疗数据的曲折之路：使用一次访谈心智模型方法改进健康数据治理和大数据请求流程的服务

• DOI: 10.1080/2573234x.2021.1992305
• 发表时间: 2021
• 期刊: Journal of Business Analytics
• 作者: Singh, Kanupriya;Jahnke, Isa;Mosa, Abu;Calyam, Prasad
• 通讯作者: Calyam, Prasad

VECTrust: trusted resource allocation in volunteer edge-cloud computing workflows

• DOI: 10.1145/3468737.3494099
• 发表时间: 2021-12
• 期刊: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing
• 作者: Ashish Pandey;P. Calyam;S. Debroy;Songjie Wang;Mauro Lemus Alarcon

Data-intensive Workflow Execution using Distributed Compute Resources

使用分布式计算资源执行数据密集型工作流程

• DOI: 10.1109/icnp.2019.8888119
• 发表时间: 2019
• 期刊: 2019 IEEE 27th International Conference on Network Protocols (ICNP
• 作者: Pandey, Ashish;Wang, Songjie;Calyam, Prasad
• 通讯作者: Calyam, Prasad

Fuzzy-Engineered Multi-Cloud Resource Brokering for Data-intensive Applications

适用于数据密集型应用程序的模糊设计多云资源代理

• DOI: 10.1109/ccgrid51090.2021.00035
• 发表时间: 2021
• 期刊: Cloud and Internet Computing (CCGrid
• 作者: Pandey, Ashish;Calyam, Prasad;Lyu, Zhen;Joshi, Trupti
• 通讯作者: Joshi, Trupti

A Formative Usability Study to Improve Prescriptive Systems for Bioinformatics Big Data

改进生物信息学大数据规范系统的形成性可用性研究

• DOI: 10.1109/bibm49941.2020.9313097
• 发表时间: 2020
• 期刊: 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM
• 作者: Singh, Kanupriya;Li, Shangman;Jahnke, Isa;Pandey, Ashish;Lyu, Zhen;Joshi, Trupti;Calyam, Prasad
• 通讯作者: Calyam, Prasad