MRI: Acquisition and Development of Mobile Edge Computing Equipment for Research and Education of Big Data Analytics with Applications in Smart Grid at PVAMU

MRI：采购和开发移动边缘计算设备，用于 PVAMU 智能电网应用大数据分析的研究和教育

• 批准号: 2018945
• 负责人: Lijun Qian
• 金额: $ 35.9万
• 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: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018945&HistoricalAwards=false
• 关键词: MRI; Acquisition; Development; Mobile; Edge

With pervasive interconnected smart objects operating together, huge amount of data has been generated that needs to be processed in an efficient and timely fashion. Mobile edge computing is promising to bring computing closer to data. This MRI project will provide much needed equipment for research in big data analytics through mobile edge computing of massive Internet-of-Things (IoT) data, and explore its applications in smart microgrid. This project will leverage the complementary expertise in two research centers of big data and smart grid at Prairie View A&M University (PVAMU) and boost the research and education in the areas of big data science, distributed machine learning, mobile edge computing, and smart power grid. If successful, this project will provide near real-time analysis and processing of massive IoT data, and foster the digital transformation of smart grid. Furthermore, this project will involve a team of researchers from PVAMU, an Historically Black College and University (HBCU), to carry out research and education activities to engage more students especially underrepresented minority students in research and provide research training. The acquisition and development of the testbeds will allow PVAMU researchers to further enhance the existing research, perform experiments and testing in the areas of big data analytics, edge computing, and smart micro-grid, and train students becoming highly-skilled future workforce, which are extremely important to the nation.Smart grid has emerged as the Internet of power supply, where a large number of IoT devices with measurement and control capability will be deployed to monitor the status of the power grid, and the collected data will allow us to better manage and control power generation, transmission, and distribution. However, systematic study of design and deployment in a distributed environment for IoT supported smart grid must be carried out to achieve the Internet-of-Energy vision. Although there are several simulation study and software-in-the-loop emulators, a real world testbed is lacking for experiments, testing and validation. To address these challenges, a team of researchers from two researcher centers, the big data research center (CREDIT center) and the smart microgrid research center (SMART center) at PVAMU will acquire mobile edge computing equipment and smart grid monitoring and data collection devices using the NSF MRI mechanism, and develop a real world testbed for big data analytics using edge computing in smart grid. The multidisciplinary team will leverage their existing research capacities and use the testbeds for more effective and efficient big data processing and predictive analysis in smart grid via mobile edge computing. The acquired equipment and testbed will establish a unique research capability at PVAMU, an HBCU. It will advance the research in mobile edge computing and big data analytics for mission-critical applications and smart grid modernization. It will also help validate the theoretical results in many current studies. It will greatly strengthen and broaden big data and smart grid research activity at PVAMU and across disciplines, complementing the existing research portfolio of the two research centers at PVAMU. Furthermore, the team is committed to make the proposed testbed available to the research community at large.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.

随着无处不在的互联智能对象一起操作，已经生成了大量的数据，需要以高效和及时的方式进行处理。移动的边缘计算有望使计算更接近数据。该MRI项目将通过海量物联网（IoT）数据的移动的边缘计算为大数据分析研究提供急需的设备，并探索其在智能微电网中的应用。该项目将利用Prairie View AM University（PVAMU）大数据和智能电网两个研究中心的互补专业知识，促进大数据科学，分布式机器学习，移动的边缘计算和智能电网领域的研究和教育。如果成功，该项目将提供对大量物联网数据的近实时分析和处理，并促进智能电网的数字化转型。此外，该项目将涉及PVAMU，一个历史上的黑人学院和大学（HBCU）的研究人员团队，开展研究和教育活动，让更多的学生，特别是代表性不足的少数民族学生参与研究，并提供研究培训。实验台的收购和开发将使PVAMU的研究人员能够进一步加强现有的研究，在大数据分析，边缘计算和智能微电网领域进行实验和测试，并培养学生成为对国家极其重要的高技能未来劳动力。智能电网已经成为电力供应的互联网，其中大量具有测控能力的物联网设备将被部署用于监测电网的状态，收集的数据将使我们能够更好地管理和控制发电，输电和配电。然而，必须对物联网支持的智能电网在分布式环境中的设计和部署进行系统研究，以实现能源互联网的愿景。虽然有几个仿真研究和软件在环仿真器，一个真实的世界的测试床是缺乏实验，测试和验证。为了应对这些挑战，来自PVAMU大数据研究中心（CREDIT中心）和智能微电网研究中心（SMART中心）两个研究中心的研究人员团队将获得使用NSF MRI机制的移动的边缘计算设备和智能电网监控和数据收集设备，并开发一个使用智能电网边缘计算进行大数据分析的真实的世界测试平台。多学科团队将利用其现有的研究能力，并通过移动的边缘计算，使用测试平台进行智能电网中更有效和高效的大数据处理和预测分析。收购的设备和试验台将在HBCU PVAMU建立独特的研究能力。它将推进移动的边缘计算和大数据分析的研究，用于关键任务应用和智能电网现代化。这也将有助于验证目前许多研究中的理论结果。它将大大加强和扩大PVAMU和跨学科的大数据和智能电网研究活动，补充PVAMU两个研究中心现有的研究组合。此外，该团队致力于使拟议的试验台提供给广大的研究社区。这个奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的知识价值和更广泛的影响审查标准。

项目成果

Efficient Privacy Preserving Edge Intelligent Computing Framework for Image Classification in IoT

用于物联网图像分类的高效隐私保护边缘智能计算框架

• DOI: 10.1109/tetci.2021.3111636
• 发表时间: 2022
• 期刊: IEEE Transactions on Emerging Topics in Computational Intelligence
• 影响因子: 5.3
• 作者: Fagbohungbe, Omobayode;Reza, Sheikh Rufsan;Dong, Xishuang;Qian, Lijun
• 通讯作者: Qian, Lijun

Comparisons Between Distributed Power Flow Controller (DPFC) and Unified Power Flow Controller (UPFC)

分布式潮流控制器（DPFC）与统一潮流控制器（UPFC）的比较

• 发表时间: 2022
• 期刊: London journal of engineering research
• 作者: Olatunde A. Adeoye, Samir I.

A Combined Chemical-Electrochemical Process to Capture CO2 and Produce Hydrogen and Electricity

• DOI: 10.3390/en14185807
• 发表时间: 2021-09
• 期刊: Energies
• 影响因子: 3.2
• 作者: N. Shamim;S. Binzaid;J. Gabitto;J. Attia