Award Abstract # 2007995
Collaborative Research: CNS Core: Small: Secure and Efficient Mobile Edge Computing in Wireless Heterogeneous Networks

NSF Org: CNS
Division Of Computer and Network Systems
Awardee: UTAH STATE UNIVERSITY
Initial Amendment Date: August 27, 2020
Latest Amendment Date: October 19, 2020
Award Number: 2007995
Award Instrument: Standard Grant
Program Manager: Alhussein Abouzeid
aabouzei@nsf.gov
 (703)292-8950
CNS
 Division Of Computer and Network Systems
CSE
 Direct For Computer & Info Scie & Enginr
Start Date: October 1, 2020
End Date: September 30, 2023 (Estimated)
Total Intended Award Amount: $249,994.00
Total Awarded Amount to Date: $249,994.00
Funds Obligated to Date: FY 2020 = $249,994.00
History of Investigator:
  • Rose Qingyang  Hu (Principal Investigator)
    rose.hu@usu.edu
Awardee Sponsored Research Office: Utah State University
1000 OLD MAIN HILL
LOGAN
UT  US  84322-1000
(435)797-1226
Sponsor Congressional District: 01
Primary Place of Performance: Utah State Univ.
4120 Old Main Hill
Logan
UT  US  84322-4120
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): SPE2YDWHDYU4
Parent UEI: SPE2YDWHDYU4
NSF Program(s): Networking Technology and Syst
Primary Program Source: 040100 NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7923, 9102
Program Element Code(s): 7363
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Jiang, Yili and Zhang, Kuan and Qian, Yi and Hu, Rose Qingyang "Efficient and Privacy-preserving Distributed Learning in Cloud-Edge Computing Systems" MiseML'21 , 2021 https://doi.org/10.1145/3468218.3469044 Citation Details
Gyawali, Sohan and Qian, Yi and Hu, Rose "Deep Reinforcement Learning Based Dynamic Reputation Policy in 5G Based Vehicular Communication Networks" IEEE Transactions on Vehicular Technology , v.70 , 2021 https://doi.org/10.1109/TVT.2021.3079379 Citation Details
Gyawali, Sohan and Qian, Yi and Hu, Rose "A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks" IEEE Transactions on Vehicular Technology , v.70 , 2021 https://doi.org/10.1109/TVT.2021.3079385 Citation Details
Wang, Qun and Zhou, Fuhui and Hu, Rose Qingyang and Qian, Yi "Energy Efficient Robust Beamforming and Cooperative Jamming Design for IRS-Assisted MISO Networks" IEEE Transactions on Wireless Communications , v.20 , 2021 https://doi.org/10.1109/TWC.2020.3043325 Citation Details
Wang, Qun and Tan, Le Thanh and Hu, Rose Qingyang and Qian, Yi "Hierarchical Energy-Efficient Mobile-Edge Computing in IoT Networks" IEEE Internet of Things Journal , v.7 , 2020 https://doi.org/10.1109/JIOT.2020.3000193 Citation Details
Ma, Xiang and Sun, Haijian and Hu, Rose Qingyang "Scheduling Policy and Power Allocation for Federated Learning in NOMA based MEC" IEEE Globecom 2020 , 2020 https://doi.org/10.1109/GLOBECOM42002.2020.9322270 Citation Details

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