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

点击翻译按钮获取中文摘要

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.