IEEE INFOCOM 2023
LoRa and LPWAN
ChirpKey: A Chirp-level Information-based Key Generation Scheme for LoRa Networks via Perturbed Compressed Sensing
Huanqi Yang and Zehua Sun (City University of Hong Kong, Hong Kong); Hongbo Liu (Electronic Science and Technology of China, China); Xianjin Xia (The Hong Kong Polytechnic University, Hong Kong); Yu Zhang and Tao Gu (Macquarie University, Australia); Gerhard Hancke and Weitao Xu (City University of Hong Kong, Hong Kong)
Speaker Huanqi Yang (City University of Hong Kong)
Huanqi Yang is currently a second-year Ph.D. student at the Department of Computer Science, City University of Hong Kong. His research interests lay in IoT security, and wireless networks.
One Shot for All: Quick and Accurate Data Aggregation for LPWANs
Ningning Hou, Xianjin Xia, Yifeng Wang and Yuanqing Zheng (The Hong Kong Polytechnic University, Hong Kong)
Speaker Ningning Hou (The Hong Kong Ploytechnic University)
Dr. Ningning Hou is a postdoctoral fellow at The Hong Kong Polytechnic University. Her research interests include Internet-of-Things, wireless sensing and networking, LPWANs, and physical layer security. She is going to join Macquarie University as a lecturer.
Recovering Packet Collisions below the Noise Floor in Multi-gateway LoRa Networks
Wenliang Mao, Zhiwei Zhao and Kaiwen Zheng (University of Electronic Science and Technology of China, China); Geyong Min (University of Exeter, United Kingdom (Great Britain))
Speaker Wenliang Mao (University of Electronic Science and Technology of China)
Wenliang Mao received the B.S. degree from the School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), in 2019, where he is currently pursuing the Ph.D. degree with the School of Computer Science and Engineering. His research interests include LoRa networks, data-driven performance modeling, and network protocols.
Push the Limit of LPWANs with Concurrent Transmissions
Pengjin Xie (Beijing University of Posts and Telecommunications, China); Yinghui Li, Zhenqiang Xu and Qian Chen (Tsinghua University, China); Yunhao Liu (Tsinghua University & The Hong Kong University of Science and Technology, China); Jiliang Wang (Tsinghua University, China)
Speaker Pengjin Xie
Pengjin Xie is currently an associate Researcher with the School of Artificial Intelligence, in Beijing
University of Posts and Telecommunications. Her current research interests include AIOT and mobile
SaTCP: Link-Layer Informed TCP Adaptation for Highly Dynamic LEO Satellite Networks
Xuyang Cao and Xinyu Zhang (University of California San Diego, USA)
Speaker Xuyang Cao (University of California San Diego)
Xuyang Cao is currently a master student in computer science at UC San Diego, advised by Professor Xinyu Zhang. Before, he did his undergraduate study in computer engineering at UC San Diego too. Xuyang's interests mainly include systems & networking, network infrastructure, and wireless communications. 😊
Achieving Resilient and Performance-Guaranteed Routing in Space-Terrestrial Integrated Networks
Zeqi Lai, Hewu Li, Yikun Wang, Qian Wu, Yangtao Deng, Jun Liu, Yuanjie Li and Jianping Wu (Tsinghua University, China)
This paper presents STARCURE, a novel resilient routing mechanism for futuristic STINs. STARCURE aims at achieving fast and efficient routing restoration while maintaining the low-latency, high-bandwidth service capabilities in failure-prone space environments. First, STARCURE incorporates a new network model, called the topology-stabilizing model (TSM) to eliminate topological uncertainty by converting the topology variations caused by various failures to traffic variations. Second, STARCURE adopts an adaptive hybrid routing scheme, collaboratively combining a constraint optimizer to efficiently handle predictable failures, together with a location-guided protection routing strategy to quickly deal with unexpected failures. Extensive evaluations driven by realistic constellation information show that STARCURE can protect routing against various failures, achieving close-to-100% reachability and better performance restoration with acceptable system overhead, as compared to other existing resilience solutions.
Speaker Zeqi Lai
Zeqi Lai is currently an assistant professor at the Institute for Network Sciences and Cyberspace at Tsinghua University. Before joining Tsinghua University, he was a senior researcher at Tencent Media Lab from 2018 to 2019 and developed the network protocols and congestion control algorithms for VooV, a large-scale commercial videoconferencing application. His research interests include next-generation Internet architecture and protocols, integrated space and terrestrial networks~(ISTN), wireless and mobile computing, and video streaming.
Network Characteristics of LEO Satellite Constellations: A Starlink-Based Measurement from End Users
Sami Ma, Yi Ching Chou, Haoyuan Zhao and Long Chen (Simon Fraser University, Canada); Xiaoqiang Ma (Douglas College, Canada); Jiangchuan Liu (Simon Fraser University, Canada)
Speaker Sami Ma (Simon Fraser University)
Sami Ma received the B.Sc. degree with distinction in Computing Science at Simon Fraser University, BC, Canada in 2019. Currently, he is continuing doctoral studies in Computing Science at Simon Fraser University. His research interests include low earth orbit satellite networks, internet architecture and protocols, deep learning, and computer vision.
FALCON: Towards Fast and Scalable Data Delivery for Emerging Earth Observation Constellations
Mingyang Lyu, Qian Wu, Zeqi Lai, Hewu Li, Yuanjie Li and Jun Liu (Tsinghua University, China)
To make big data delivery for emerging EO constellations fast and scalable, we propose FALCON, a multi-path EO delivery framework that wisely exploits diverse paths in broadband constellations to collaboratively deliver EO data effectively. Specifically, we formulate the constellation-wide EO data multipath download (CEOMP) problem, which aims at minimizing the delivery completion time of requested data for all EO sources. We prove the hardness of solving CEOMP, and further present a heuristic multipath routing and bandwidth allocation mechanism to tackle the technical challenges caused by time-varying satellite dynamics and flow contention, and solve the CEOMP problem efficiently. Evaluation results based on public orbital data of real EO constellations show that as compared to other state-of-the-art approaches, FALCON can reduce at least 51% delivery completion time for various data requests in large EO constellations.
Speaker Mingyang Lyu (Tsinghua University)
Mingyang Lv received the B.S. degree in Network Engineering from Sun Yat-Sen University in 2018. He is currently working toward the M.S. degree in the institute for Network Sciences and Cyberspace at Tsinghua university. His research interests mainly include big data distribution and routing in integrated space and terrestrial networks (ISTN).
LARRI: Learning-based Adaptive Range Routing for Highly Dynamic Traffic in WANs
Minghao Ye (New York University, USA); Junjie Zhang (Fortinet, Inc., USA); Zehua Guo (Beijing Institute of Technology, China); H. Jonathan Chao (NYU Tandon School of Engineering, USA)
Speaker Minghao Ye (New York University)
Minghao Ye is a 4th-year Ph.D. Candidate at the Department of Electrical and Computer Engineering of New York University (NYU), working with Professor H. Jonathan Chao at the NYU High-Speed Networking Lab. His research mainly focuses on traffic engineering, network optimization, software-defined networks, and machine learning for networking.
A Learning Approach to Minimum Delay Routing in Stochastic Queueing Networks
Xinzhe Fu (Massachusetts Institute of Technology, USA); Eytan Modiano (MIT, USA)
Speaker Eytan Modiano
Eytan Modiano is a Professor in the Laboratory for Information and Decision Systems (LIDS) at MIT.
Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences
János Tapolcai and Péter Babarczi (Budapest University of Technology and Economics, Hungary); Pin-Han Ho (University of Waterloo, Canada); Lajos Rónyai (Budapest University of Technology and Economics (BME), Hungary)
Speaker János Tapolcai (Budapest University of Technology and Economics)
János Tapolcai received an MSc degree in technical informatics and a Ph.D. degree in computer science from the Budapest University of Technology and Economics (BME), Budapest, in 2000 and 2005, respectively, and a D.Sc. degree in engineering science from the Hungarian Academy of Sciences (MTA) in 2013. He is a Full Professor with the High-Speed Networks Laboratory, Department of Telecommunications and Media Informatics, BME. He has authored over 150 scientific publications.
He received several Best Paper Awards, including ICC'06, DRCN'11, HPSR'15, and NaNa'16. He won the MTA Lendület Program, the Google Faculty Award in 2012, and Microsoft Azure Research Award in 2018. He is a TPC member of leading conferences, e.g., IEEE INFOCOM 2012-, and the general chair of ACM SIGCOMM 2018.
Impact of International Submarine Cable on Internet Routing
Honglin Ye (Tsinghua University, China); Shuai Wang (Zhongguancun Laboratory, China); Dan Li (Tsinghua University, China & Zhongguancun Laboratory, China)
Speaker Honglin Ye (Tsinghua University)
Honglin Ye is currently working toward the M.S. degree in the institute for Network Sciences and Cyberspace at Tsinghua university. Her research interests mainly include submarine cable measurement and inter-domain routing.