CAREER: Theory and Algorithms for Efficient Control of Wireless Networks with Jointly Optimized Performance: High Throughput, Low Delay, and Low Complexity
Synopsis
With the advent of smart devices and the Internet of things, wireless technology has spawned a plethora of services that span business, science and engineering, entertainment, safety and security, health monitoring, and cover a large portion of our social interactions. Due to the prevalence of these new services, today's wireless networks are witnessing not only an unprecedented growth in the volume of traffic, but also a significant change in the types of traffic (e.g., a much higher percentage of voice/video traffic with more stringent delay requirements). These new trends require next-generation wireless networks to provide not only high data rates (tens of gigabits per second), but also ultra-low latencies (sub-millisecond). Moreover, as wireless networks grow and support an increasingly large number of users, network control algorithms must also incur low complexity in order to be implemented in practice. However, the question of how to simultaneously achieve high throughput, low delay and low complexity remains largely open. Addressing this major research challenge is a main goal of this project. Not only is this research expected to substantially advance our understanding of designing efficient control algorithms for wireless networks with jointly optimized performance, but it would also expand/create the much-needed theoretical foundations for developing simple and practical protocols to optimize the key performance metrics needed in the design of next-generation wireless networks. This research will also be closely integrated with a comprehensive educational plan, which is focused on providing research experiences to undergraduate and K-12 students, recruiting and training underrepresented students, and engaging in curriculum development activities.
The goal of this project is to create new theoretical foundations for designing provably efficient network control algorithms that perform well in all three dimensions of throughput, delay, and complexity. Specifically, this research will be carried out around three main thrusts: (i) it focuses on intra-cell control for a multi-channel cellular network, and aims to build a theoretical framework for designing low-complexity scheduling algorithms with provably guaranteed optimal throughput and optimal (or near-optimal) large-deviations delay rate-function; (ii) it considers a more challenging setting of network-wide control for larger systems (e.g., a dense multi-cell system or an ad hoc wireless network), and aims to develop a new node-based approach for designing efficient scheduling algorithms with provable throughput and evacuation time performance; and (iii) it considers distributed network-side control and aims to design low-complexity algorithms that achieve high throughput and low delay.
This project is supported by the National Science Foundation (NSF) under Grant CNS-2112694 (old: CNS-1651947) from 5/1/2017 to 4/30/2023. [NSF link] [old link]
Fengjiao Li (Ph.D., Spring 2018 - Fall 2022; Dept. of Computer Science Ph.D. Research Award in 2023; IEEE/IFIP WiOpt 2022 Best Student Paper Award; Dr. Dennis G. Kafura Graduate Fellowship in Computer Science in 2022; N2Women Young Researcher Fellowship in 2020; Scott Hibbs Future of Computing Award in 2020; IEEE INFOCOM 2019 Best Paper Award; IEEE INFOCOM 2019 Best-in-Session Presentation Award; now Assistant Professor at Shanxi University in China)
Gamal Sallam (Ph.D., July 2020; Temple University Doctoral Dissertation Completion Grant in 2020; CST Graduate Research Assistant Award in 2019; CIS Graduate Research Assistant Award in 2019; IEEE INFOCOM 2018 Best-in-Session Presentation Award; now Research Scientist at Facebook)
Yu Sang (Ph.D., June 2019; Presidential Fellowship from Temple University in 2014; Scott Hibbs Future of Computing Award in 2017; now Research Scientist at Facebook)
Former Undergraduate Students
Jeremy Sanchez (BS in CS, NSF REU)
Rui Wang (Virginia Tech, Undergrad Researcher; joining UIUC in Fall 2022 as a Master's student)
Chengpei Wu (Virginia Tech, Undergrad Researcher)
Helene Mbonda (Virginia Tech, Undergrad Researcher)
F. Li, X. Zhou, and B. Ji, “(Private) Kernelized Bandits with Distributed Biased Feedback,” Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), vol. 7, no. 1, pp 1–47, March 2023. [Link]
Z. Liu, B. Li, Z. Zheng, T. Hou, and B. Ji, “Towards Optimal Tradeoff Between Data Freshness and Update Cost in Information-update Systems,” IEEE Internet of Things Journal (IoT-J), accepted, December 2022. [Technical Report (arXiv)]
D. Cheng, X. Zhou, and B. Ji, “Understanding the Role of Feedback in Online Learning with Switching Costs,” Proceedings of ICML 2023, Honolulu, HI, July 2023.
F. Li, X. Zhou, and B. Ji, “(Private) Kernelized Bandits with Distributed Biased Feedback,” Proceedings of ACM SIGMETRICS 2023, Orlando, FL, June 2023. [Technical Report (arXiv)]
S. Zhang, B. Ji, K. Zeng, and H. Zeng “Realizing Uplink MU-MIMO Communication in mmWave WLANs: Bayesian Optimization and Asynchronous Transmission,” Proceedings of IEEE INFOCOM 2023, New York, May 2023.
X. Zhou and B. Ji, “On Kernelized Multi-Armed Bandits with Constraints,” Proceedings of NeurIPS 2022, New Orleans, LA, November 2022. [Technical Report (arXiv)]
M. Yu, B. Ji, H. Rajan, and J. Liu, “On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention,” Proceedings of ACM MobiHoc 2022, Seoul, South Korea, October 2022. [Technical Report (arXiv)]
F. Li, X. Zhou, and B. Ji, “Differentially Private Linear Bandits with Partial Distributed Feedback,” Proceedings of IEEE/IFIP WiOpt 2022, Turin, Italy, September 2022. [Technical Report (arXiv)] (Best Student Paper Award)
B. Li, B. Ji, and A. Eryilmaz, “Age-Efficient Scheduling in Communication Networks,” in book “Age of Information: Foundations and Applications,” Edited by Walid Saad, Harpreet Dhillon, Nikolaos Pappas, Mohamed A. Abd-Elmagid, and Bo Zhou, Cambridge University Press, February 2023. [PDF] [link]
G. Sallam, Z. Zheng, and B. Ji, “Placement and Allocation of Virtual Network Functions: Multi-dimensional Case,” IEEE Transactions on Mobile Computing (TMC), accepted, February 2022. [Technical Report (arXiv)]
M. Yu, J. Liu, C. Wu, B. Ji, and E. S. Bentley, “Toward Efficient Online Scheduling for Distributed Machine Learning Systems,” IEEE Transactions on Network Science and Engineering (TNSE), accepted, July 2021. [Technical Report (arXiv)]
Z. Liu, B. Li, Z. Zheng, Y. T. Hou, and B. Ji, “Towards Optimal Tradeoff Between Data Freshness and Update Cost in Information-update Systems,” ICCCN 2022, Virtual Event, July 2022. (invited paper) [Technical Report (arXiv)]
M. Yu, Y. Tian, B. Ji, C. Wu, H. Rajan, and J. Liu, “GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs,” IEEE INFOCOM 2022, Virtual Event, May 2022. [Technical Report (arXiv)]
F. Li, J. Liu, and B. Ji, “Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach,” Proceedings of IEEE MASS 2021, Virtual Event, October 2021. [Technical Report (arXiv)]
Z. Liu, Y. Sang, B. Li, and B. Ji, “A Worst-Case Approximate Analysis of Peak Age-of-Information via Robust Queueing Approach,” Proceedings of IEEE INFOCOM 2021, Virtual Event, May 2021. [PDF]
M. Yu, C. Wu, B. Ji, and J. Liu, “A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling,” Proceedings of IEEE INFOCOM 2021, Virtual Event, May 2021. [Technical Report (arXiv)]
J. Chen, X. Qin, G. Zhu, B. Ji, and B. Li, “Motion-Prediction-based Wireless Scheduling for Multi-User Panoramic Video Streaming,” Proceedings of IEEE INFOCOM 2021, Virtual Event, May 2021. [PDF]
Z. Liu, L. Huang, B. Li, and B. Ji, “Anti-Aging Scheduling in Single-Server Queues: A Systematic and Comparative Study,” Journal of Communications and Networks, vol. 23, no. 2, pp. 91-105, April 2021. [Technical Report (arXiv)]
G. Sallam and B. Ji, “Joint Placement and Allocation of VNF Nodes with Budget and Capacity Constraints,” IEEE/ACM Transactions on Networking (ToN), vol. 29, no. 3, pp. 1238-1251, June 2021. [Technical Report (arXiv)]
F. Li, Y. Sang, Z. Liu, B. Li, H. Wu, and B. Ji, “Waiting but not Aging: Optimizing Information Freshness Under the Pull Model,” IEEE/ACM Transactions on Networking (ToN), vol. 29, no. 1, pp. 465-478, Feb. 2021. [Technical Report (arXiv)]
B. Li, J. Liu, and B. Ji, “Low-Overhead Wireless Uplink Scheduling for Large-Scale Internet-of-Things,” IEEE Transactions on Mobile Computing (TMC), vol. 20, no. 2, pp. 577-587, 1 Feb. 2021.
L. P. Qian, Y. Wu, B. Ji, and X. Shen, “Optimal ADMM-based Spectrum and Power Allocation for Heterogeneous Small-Cell Networks with Hybrid Energy Supplies,” IEEE Transactions on Mobile Computing (TMC), vol. 20, no. 2, pp. 662-677, 1 Feb. 2021.
G. Sallam, Z. Zheng, J. Wu, and B. Ji, “Robust Sequence Submodular Maximization,” Proceedings of NeurIPS 2020, Vancouver, Canada, December 2020. [Technical Report (arXiv)]
Y. Chen, J. Wu, and B. Ji, “Optimizing Flow Bandwidth Consumption with Traffic-diminishing Middlebox Placement,” Proceedings of ICPP 2020, Edmonton, AB, Canada, August 2020.
Z. Liu, L. Huang, B. Li, and B. Ji, “Anti-Aging Scheduling in Single-Server Queues: A Systematic and Comparative Study,” Proceedings of IEEE INFOCOM 2020, Workshop on Age of Information (AoI), Toronto, Canada, July 2020. [Technical Report (arXiv)]
F. Li, J. Liu, and B. Ji, “Combinatorial Sleeping Bandits with Fairness Constraints,” IEEE Transactions on Network Science and Engineering (TNSE), vol. 7, no. 3, pp. 1799-1813, 1 July-Sept. 2020. (Invited Fast Track Submission) [Technical Report (arXiv)]
Y. Chen, J. Wu, and B. Ji, “Deploying Virtual Network Functions With Non-Uniform Models in Tree-Structured Networks,” IEEE Transactions on Network and Service Management (TNSM), vol. 17, no. 4, pp. 2260-2274, Dec. 2020.
H. Shakhatreh, A. Khreishah, and B. Ji, “UAVs to the Rescue: Prolonging the Lifetime of Wireless Devices Under Disaster Situations,” IEEE Transactions on Green Communications and Networking (TGCN), vol. 3, no. 4, pp. 942-954, 2019.
L. P. Qian, F. Ai, Y. Huang, Y. Wu, B. Ji, and Z. Shi, “Optimal SIC Ordering and Computation Resource Allocation in MEC-aware NOMA NB-IoT Networks,” IEEE Internet of Things Journal, vol. 6, no. 2, pp. 2806-2816, April 2019.
L. P. Qian, Y. Wu, B. Ji, L. Huang, and D. H. K. Tsang, “HybridIoT: Integration of Hierarchical Multiple Access and Computation Offloading for IoT-Based Smart Cities,” IEEE Network, vol. 33, no. 2, pp. 6-13, March/April 2019.
G. Sallam, Z. Zheng, and B. Ji, “Placement and Allocation of Virtual Network Functions: Multi-dimensional Case,” Proceedings of IEEE ICNP 2019, Chicago, Illinois, October 2019. [Technical Report (arXiv)]
Z. Liu and B. Ji, “Towards the Tradeoff Between Service Performance and Information Freshness,” Proceedings of IEEE ICC 2019, Shanghai, China, May 2019. [Technical Report (arXiv)]
F. Li, J. Liu, and B. Ji, “Combinatorial Sleeping Bandits with Fairness Constraints,” Proceedings of IEEE INFOCOM 2019, Paris, France, April/May 2019. [Technical Report (arXiv)] (Best Paper Award; Best-in-Session Presentation Award)
G. Sallam and B. Ji, “Joint Placement and Allocation of Virtual Network Functions with Budget and Capacity Constraints,” Proceedings of IEEE INFOCOM 2019, Paris, France, April/May 2019. [Technical Report (arXiv)]
Y. Chen, J. Wu, B. Ji, “Virtual Network Function Deployment in Tree-structured Networks,” Proceedings of IEEE ICNP 2018, Cambridge, UK, September 2018.
N. Lu, B. Ji, and B. Li, “Age-based Scheduling: Improving Data Freshness for Wireless Real-Time Traffic,” Proceedings of ACM MobiHoc 2018, Los Angeles, California, June 2018. [PDF]
B. Li, B. Ji, and J. Liu, “Efficient and Low-Overhead Uplink Scheduling for Large-Scale Wireless Internet-of-Things,” Proceedings of IEEE WiOpt 2018, Shanghai, China, May 2018. [PDF]
K. Chi, L. Wu, X. Du, G. Yin, J. Wu, B. Ji, and X. Hei, “Enabling Fair Spectrum Sharing between Wi-Fi and LTE-Unlicensed,” Proceedings of IEEE ICC 2018, Kansas City, MO, May 2018.
G. Sallam, G. R. Gupta, B. Li, and B. Ji, “Shortest Path and Maximum Flow Problems Under Service Function Chaining Constraints,” Proceedings of IEEE INFOCOM 2018, Honolulu, HI, April 2018. [PDF] (Best-in-Session Presentation Award)
Y. Sang, G. R. Gupta, and B. Ji, “Node-based Service-Balanced Scheduling for Provably Guaranteed Throughput and Evacuation Time Performance,” IEEE Transactions on Mobile Computing (TMC), vol. 17, no. 8, pp. 1938-1951, 2018. [Technical Report (arXiv)]
Y. Sang, B. Li, and B. Ji, “The Power of Waiting for More than One Response in Minimizing the Age-of-Information,” IEEE GLOBECOM 2017, Singapore, December 2017. [Technical Report (arXiv)]
H. Shakhatreh, A. Khreishah, and B. Ji, “Providing Wireless Coverage to High-rise Buildings Using UAVs,” IEEE ICC 2017, Paris, France, May 2017.
Educational Activities and Recognitions
Li (Graduate Research Assistant, female) received the Ph.D. Research Award from Department of Computer Science at Virginia Tech in 2023.
PI Ji received the College of Engineering Dean's Award for Faculty Fellow at Virginia Tech in 2023.
The PI received Excellent Editor Award from the IEEE Transactions on Network Science and Engineering in 2022.
Our paper “Differentially Private Linear Bandits with Partial Distributed Feedback” by PI Ji and Li (Ji’s Graduate Research Assistant, female), as well as their collaborator Prof. Xingyu Zhou, received the IEEE/IFIP WiOpt 2022 Best Student Paper Award.
PI Ji advised three high school students to conduct research.
PI Ji served as member of ACM SIGMETRICS Committee on Student Engagement, participated in formalizing and establishing the continuity of best practices inside the SIGMETRICS community, with a focus on promoting the participation from students who belong to under-represented groups.
PI Ji was nominated for the College of Engineering Faculty Fellow at Virginia Tech in 2021.
PI Ji was nominated for the CST Distinguished Faculty Mentoring Award at Temple University in 2019.
PI Ji was nominated for the CST Distinguished Faculty Teaching Award at Temple University in 2018.
Skylar Liang (Undergraduate Research Assistant, female) will join Virginia Tech as a Master's student in Spring 2023.
Rui Wang (Undergraduate Research Assistant) will join University of Illinois Urbana-Champaign as a Master's student in Fall 2022.
Fengjiao Li (Graduate Research Assistant, female) received the Dr. Dennis G. Kafura Graduate Fellowship in Computer Science in 2022.
Zhongdong Liu (Graduate Research Assistant) attended IEEE INFOCOM 2021 and presented his work at the conference.
Fengjiao Li (Graduate Research Assistant, female) attended IEEE MASS 2021 and presented her work at the conference.
Zhongdong Liu (Graduate Research Assistant) attended the AoI Workshop coloated with IEEE INFOCOM 2020 and presented his work at the workshop.
Gamal Sallam (Graduate Research Assistant) attended NeurIPS 2020 and presented his work at the conference.
Fengjiao Li (Graduate Research Assistant, female) gave a talk at the College of Science and Technology Graduate Research Mixer event in Fall 2019. The purpose of the event is to increase inter-departmental collaboration through new and innovative interdisciplinary projects.
Hoang Ho (Undergraduate Research Assistant, female) joined University of Massachusetts Amherst as a PhD student in Fall 2019.
Aamir Mandviwalla (Undergraduate Research Assistant) joined Rensselaer Polytechnic Institute as a PhD student in Fall 2019.
Chelsea Zackey (Undergraduate Research Assistant, female) joined Temple University as a Master's student in Fall 2019.
Keita Ohshiro (Undergraduate Research Assistant) joined New York University as a Master's student in Fall 2019.
Fengjiao Li (Graduate Research Assistant, female) and Zhongdong Liu (Graduate Research Assistants) attended the 2019 IMACCS Workshop in Columbus, OH and presented their posters. Chelsea Zackey (Undergraduate Research Assistant, female) also attended the workshop.
Fengjiao Li (Graduate Research Assistant, female) attended IEEE INFOCOM 2019 and presented her work at the conference. Fengjiao received the Best-in-Session Presentation Award for her excellent presentation. Her paper also received the IEEE INFOCOM 2019 Best Paper Award.
Zhongdong Liu (Graduate Research Assistant) attended IEEE ICC 2019 and presented his work at the conference.
Gamal Sallam (Graduate Research Assistant) received the Department of Computer and Information Sciences Outstanding Graduate Research Assistant Award in Spring 2019.
Keita Ohshiro (Undergraduate Research Assistant) received the Scott Hibbs Future of Computing Award from College of Science and Technology at Temple University in Spring 2019.
Keita Ohshiro (Undergraduate Research Assistant) participated in the Undergraduate Research Symposium at Temple University and presented a poster in Fall 2018. Keita also appeared in the final list for receiving awards.
Yeahuay Wu (Undergraduate Research Assistant, female) joined University of Massachusetts Amherst as a PhD student in Fall 2018.
Fengjiao Li (female), Zhongdong Liu, and Gamal Sallam (Graduate Research Assistants) attended the 2018 IMACCS Workshop in Columbus, OH.
Gamal Sallam (Graduate Research Assistant) attended IEEE INFOCOM 2018 and presented his work at the conference. Gamal received the Best-in-Session Presentation Award for his excellent presentation.
PI Ji participated in Center for the Enhancement of Engineering Diversity (CEED)'s Women's Preview Weekend event.
PI Ji participated in Center for the Enhancement of Engineering Diversity (CEED)'s Galipatia Slush Rush event.
PI Ji gave invited talks at various conferences (CISS 2021 and IEEE Sarnoff 2019) and universities (Gonzaga University, Old Dominion University, University of Massachusetts Dartmouth, University at Buffalo, Virginia Tech, University of Delaware, Yale University, Villanova University, etc.)
Fengjiao Li (Graduate Research Assistant, female), Zhongdong Liu (Graduate Research Assistant), and Keita Ohshiro (Undergraduate Research Assistant) participated in the Start Talking Science event, which is a free public event where STEM researchers present posters detailing their research to a general audience, including local K-12 students in the greater Philadelphia area. This event aims to foster insightful conversations and connections and increase public interest in the cutting-edge research taking place right here in Philadelphia.