Collaborative Research: CNS Core: Small: Secure and Efficient Mobile Edge Computing in Wireless Heterogeneous Networks

合作研究： CNS 核心：小型：无线异构网络中安全高效的移动边缘计算

• 批准号: 2007995
• 负责人: Rose Qingyang Hu
• 金额: $ 25万
• 依托单位: Utah State 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: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2007995&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Small

Future wireless networks will support massive energy-limited computation-constrained user equipment that are often required to execute latency sensitive yet computation-intensive tasks. Although technologies that can elevate local device computation capability and battery capacity have been substantially pushed forward, there still exists a huge gap between the high computation/processing demands and the low computation/battery capacities in user equipment. Mobile edge computing (MEC) allows user equipment to offload partial or complete computation-intensive tasks to the edge computing servers to save power and reduce latency. Inspired by recent advances in wireless technologies and challenges, the proposed research aims to explore a novel framework that can jointly consider communications and computations in a mobile edge computing-based wireless heterogeneous network to realize secure and efficient offloading and achieve desirable trade-offs among computation throughput, computation efficiency, latency, and user fairness. The proposed research activities have significant potentials to revolutionize the next generation wireless network design by jointly considering edge computations and communications in delivering secure, latency critical, computation-intensive applications such as augmented reality/virtual reality, connected and autonomous vehicle, and remote medical diagnosis. It can significantly facilitate the understanding in the field of emerging mobile edge networks, which will play a key role in the modem society to realize smart environments with computation intensive mobile applications. The proposed research framework develops secure multiple access schemes during offloading, computation coordination and scheduling schemes for selecting user equipment and computation tasks to offload. The research will identify unique technical challenges and explore many new aspects in the mobile edge computing enabled wireless heterogenous networks, including non-orthogonal multiple access, computing offloading mode selection, success interference cancellation decoding order design, hybrid multiple access analysis, and heterogeneous MEC coordination, driven by joint consideration on security, efficiency, and user fairness. The theoretical framework formulation and analysis, engineering design guidelines for practical implementation and deployment will be obtained, and prototyping/simulation tools will be shared with the scientific research and engineering communities. The success of this project can greatly advance the understanding of the critical issues in the mobile edge computing-based wireless network design and contribute a new resource allocation framework that can remarkably improve the performance of future wireless network computing. The project will also both undergraduate and graduate students research opportunities with developing and deploying new wireless network technologies, thus serving the growing need for educating and training students, especially female students and students from underrepresented groups.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.

未来的无线网络将支持大规模的能源限制计算受限的用户设备，这些用户设备通常需要执行延迟敏感但计算密集型任务。尽管可以将可以提升本地设备计算功能和电池容量的技术实质上推动，但在高计算/处理需求与用户设备中低的计算/电池容量之间仍然存在巨大差距。移动边缘计算（MEC）允许用户设备将部分或完整的计算密集型任务卸载到边缘计算服务器，以节省功率并减少延迟。受到无线技术和挑战的最新进展的启发，拟议的研究旨在探索一个新颖的框架，该框架可以在基于移动边缘计算的基于移动边缘计算的无线异质网络中共同考虑通信和计算，以实现安全有效的卸载并实现可取的折衷，并在计算吞吐量，计算效率，延迟，延迟和用户公平。 拟议的研究活动具有巨大的潜力，可以通过共同考虑边缘计算和通信来彻底改变下一代无线网络设计，以提供安全，延迟关键，计算密集型应用，例如增强现实/虚拟现实/虚拟现实，连接和自动驾驶汽车以及远程医疗诊断。它可以显着促进新兴移动边缘网络领域的理解，这将在现代社会中发挥关键作用，以通过计算密集的移动应用程序实现智能环境。拟议的研究框架在卸载，计算协调和调度方案过程中开发了安全的多个访问方案，以选择用户设备和计算任务以卸载。这项研究将确定独特的技术挑战，并探索移动边缘计算中的许多新方面，可以实现无线异质网络，包括非正交的多重访问，计算卸载模式选择，成功干扰取消解码订单设计，混合多重访问分析和异构性无偶然的MEC协调，以及由安全性考虑安全性，对安全性，对安全性，EFFIESSION和EFFICE，EFFIESSINES和用户公平性和用户公平性。 将获得理论框架公式和分析，工程设计指南，用于实践和部署，并将与科学研究和工程社区共享原型设计/仿真工具。该项目的成功可以大大提高人们对基于移动边缘计算的无线网络设计中关键问题的理解，并贡献一个新的资源分配框架，可以显着提高未来无线网络计算的性能。该项目还将在开发和部署新的无线网络技术方面研究本科和研究生研究机会，从而满足对教育和培训学生的日益增长的需求，尤其是女学生和来自代表性不足的小组的学生。这项奖项反映了NSF的法定任务，并通过基金会的知识优点和广泛的影响来评估NSF的法定任务，并被认为是值得的支持。

项目成果

Energy Efficient Robust Beamforming and Cooperative Jamming Design for IRS-Assisted MISO Networks

• DOI: 10.1109/twc.2020.3043325
• 发表时间: 2021-04-01
• 期刊: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
• 影响因子: 10.4
• 作者: Wang, Qun;Zhou, Fuhui;Qian, Yi
• 通讯作者: Qian, Yi

Cooperative Task Allocation in Edge Computing Assisted Vehicular Crowdsensing

• DOI: 10.1109/globecom46510.2021.9685136
• 发表时间: 2021-12
• 期刊: 2021 IEEE Global Communications Conference (GLOBECOM)
• 作者: Yili Jiang;Kuan Zhang;Y. Qian;R. Hu

Privacy-preserving data deduplication in edge-assisted mobile crowdsensing

边缘辅助移动群智感知中的隐私保护重复数据删除

• DOI: 10.1504/ijmis.2022.121283
• 发表时间: 2022
• 期刊: International Journal of Multimedia Intelligence and Security
• 作者: Jiang, Yili;Zhang, Kuan;Qian, Yi;Hu, Rose Qingyang
• 通讯作者: Hu, Rose Qingyang

A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks

• DOI: 10.1109/tvt.2021.3079385
• 发表时间: 2021-06
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: Sohan Gyawali;Y. Qian;R. Hu

Scheduling Policy and Power Allocation for Federated Learning in NOMA Based MEC

• DOI: 10.1109/globecom42002.2020.9322270
• 发表时间: 2020-01-01
• 期刊: 2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
• 作者: Ma, Xiang;Sun, Haijian;Hu, Rose Qingyang
• 通讯作者: Hu, Rose Qingyang