NeTS: Small: Collaborative Research: Towards Adaptive and Efficient Wireless Computing Networks
Personnel
Principal Investigators
Bin Li, Assistant Professor, University of Rhode Island
Lei Ying, Professor, University of Michigan, Ann Arbor
Graduate Students
Xudong Qin (University of Rhode Island)
Noah Johnson (University of Rhode Island)
Pengfei Jiang (Arizona State University)
Project Goals
Today's mobile devices are not merely smart, they are becoming intelligent as artificial intelligence applications
such as Facebook Caffe2 and Google Tensor-Flow Lite are being pushed into mobile devices and as mobiles devices are
being integrated into the cloud-fog-mobile architecture. This calls for efficient and adaptive computing/communication
co-design of wireless networks to optimize application-level latency (including both communication latency and computing times) and to achieve energy efficiency (considering energy consumed by both communications and computing). This project develops fundamental theories and novel architectures of low-latency, energy-efficient, and computing-centric wireless networks to support emerging mobile intelligence applications. Theories and algorithms developed by the PIs are constantly integrated into the undergraduate and graduate courses taught at the two universities. This project also provides hand-on experiences to undergraduate and high school students with state-of-the-art wireless technologies.
Computing/communication co-design, while new for wireless networks, is a central topic in data center networks. However, the
proposed solutions, while inspiring, are not directly applicable to wireless computing networks because of the unique
features of wireless networks such as wireless interference, channel fading and limited energy. This project focuses
provably optimal mechanisms that dynamically and adaptively schedule computing tasks and data transmissions to meet
application-level performance requirements, and consists of three interdependent thrusts.
(I) Optimal computing/communication co-design. This thrust develops mathematical models and theoretical
limits of wireless computing networks.
(II) Robust computing/communication co-design. This thrust focuses on robust computing and communication
co-design that achieves desired performance with imperfect state information and under unavoidable short-term system overload.
(III) Learning-aided adaptive computing/communication co-design. This thrust further improves the performance of wireless computing networks by leveraging both historical data and predictable user behaviors.
Publications
Xudong Qin, Bin Li, Lei Ying, Distributed Threshold-based Offloading for Large-Scale Mobile Cloud Computing, In Proc. IEEE International Conference on Computer Communications (INFOCOM), May, 2021. [ Acceptance rate: 19.9%]
Jiangong Chen, Xudong Qin, Guangyu Zhu, Bo Ji, Bin Li, Motion-Prediction-based Wireless Scheduling for Multi-User Panoramic Video Streaming, In Proc. IEEE International Conference on Computer Communications (INFOCOM), May, 2021. [ Acceptance rate: 19.9%]
Bin Li, Efficient Learning-based Scheduling for Information Freshness in Wireless Networks, In Proc. IEEE International Conference on Computer Communications (INFOCOM), May, 2021. [ Acceptance rate: 19.9%]
Zhongdong Liu, Yu Sang, Bin Li, Bo Ji, A Worst-Case Approximate Analysis of Peak Age-of-Information Via Robust Queueing Approach, In Proc. IEEE International Conference on Computer Communications (INFOCOM), May, 2021. [ Acceptance rate: 19.9%]
Jiangong Chen, Bin Li, R. Srikant, Thompson-Sampling-Based Wireless Transmission for Panoramic Video Streaming, In WiOpt Workshop on Machine Learning in Wireless Communications (WMLC), June, 2020. (invited paper)
D Narasimha, S Shakkottai, L Ying, A mean field game analysis of distributed mac in ultra-dense multichannel wireless networks, IEEE/ACM Transactions on Networking (ToN), 2020.
W. Wang and L. Ying, Learning Parallel Markov Chains over Unreliable Wireless Channels, 54th Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, USA, 2020.
P. Jiang and L. Ying, An Optimal Stopping Approach for Iterative Training in Federated Learning, 2020 54th Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, USA, 2020.
Bin Li, Atilla Eryilmaz, R. Srikant, Emulating Round-Robin for Serving Dynamic Flows over Wireless Fading Channels, In ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC), October, 2020. [ Acceptance rate: 15%]
Zhengxiong Yuan, Bin Li, Jia Liu, Can We Improve Information Freshness with Predictions in Mobile Crowd-Learning?, in Proc. IEEE INFOCOM 2020 Age of Information Workshhop, Toronto, Canada, July, 2020.
Zhongdong Liu, Liang Huang, Bin Li, Bo Ji, Anti-Aging Scheduling in Single-Server Queues: A Systematic and Comparative Study/, in Proc. IEEE INFOCOM 2020 Age of Information Workshhop, Toronto, Canada, July, 2020.
Xiangqi Kong, Ning Lu, Bin Li, Optimal Scheduling for Unmanned Aerial Vehicle Networks with Flow-Level Dynamics, accepted by IEEE Transactions on Mobile Computing (TMC), 2019.
Bin Li, Jia Liu, Bo Ji, Low-Overhead Wireless Uplink Scheduling for Large-Scale Internet-of-Things, accepted by IEEE Transactions on Mobile Computing (TMC), 2019. (An earlier version of this paper has appeared in the Proc. WiOpt 2018)
D. Narasimha, S. Shakkottai and L. Ying, A Mean Field Game Analysis of Distributed MAC in Ultra-Dense Multichannel Wireless Networks, In ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC), Catania, Italy, July, 2019.
Bin Li, Optimal Offloading for Dynamic Compute-Intensive Applications in Wireless Networks, In Proc. IEEE Conference on Global Communications Conference (GLOBECOM), Waikoloa, Hawaii, December, 2019.
Bin Li, Jia Liu, Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?, In International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Avignon, France, June, 2019.
Xudong Qin, Weijian Xu, Bin Li, Low-Complexity Joint Offloading and Wireless Scheduling for Parallel Computing with Deadlines, In International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Avignon, France, June, 2019.
Broader Impact and Outreach Activities
[September 2020]: Dr. Lei Ying co-organized a 2-day workshop on Epidemics, Opinion, and (Mis)Information: The Analytic Foundations of Dynamics over Networks
[September 2020]: Dr. Bin Li co-organized URI second Immerse-a-thon event for exploring virtual/augmented applications beyond gaming, and delivered the talk on the virtual/augmented reality technology.
[September 2020]: Dr. Bin Li was invited to be a panelist for the panel on AR/VR/XR over wireless networks: challenges and opportunities in the 21st IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WOWMOM 2020).
[April 2019]: Dr. Bin Li's group demonstrated various wireless virtual/augmented reality applications for K-12 students in Alan Shawn Feinstein Middle School of Coventary. Thanks Xiangqi and Xudong.
[April 2019]: Dr. Bin Li's group demonstrated various wireless virtual/augmented reality applications for K-12 students in National Biomechanics Day. Thanks Xiangqi, Xudong, and Noah.
[April 2019]: Dr. Bin Li's group demonstrated various wireless virtual/augmented reality applications for K-12 students in Kingston Hill Academy Elementary School. Thanks Xiangqi and Xudong.
[March 2019]: Dr. Bin Li's group demonstrated various virtual/augmented reality applications for local residents and K-12 students in URI Brain Fair. Thanks Xiangqi, Xudong, and Noah. The news appeared in URI College of Engineering website
[March 2019]: Dr. Bin Li organized URI first Immerse-a-thon event for exploring virtual/augmented applications beyond gaming. Thanks Deedee Chatham (director of Entrepreneurship, Innovation and Undergraduate Research at URI) for providing logistics support and promoting this event as well as all speakers, mentors, and judges. The news appeared in URI College of Engineering website and Rhode Island Inno
