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

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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.