IEEE INFOCOM 2023
SkyNet: Multi-Drone Cooperation for Real-Time Identification and Localization
Junkun Peng (Tsinghua University, China); Qing Li (Peng Cheng Laboratory, China); Yuanzheng Tan (Sun Yat-Sen University, China); Dan Zhao (Peng Cheng Laboratory, China); Zhenhui Yuan (Northumbria University, United Kingdom (Great Britain)); Jinhua Chen (Sun Yat-Sen University, China); Hanling Wang (Tsinghua University & Peng Cheng Laboratory, China); Yong Jiang (Graduate School at Shenzhen, Tsinghua University, China)
Speaker Junkun Peng (Tsinghua University)
Junkun Peng received his B.S. degree in Information Management and Information Systems from Shanghai University, China, in 2015.
He is currently pursuing a Ph.D. in Computer Science at Tsinghua University, China.
His research focuses on real-time video transmission and analysis, and robot learning.
A2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems
Andrea Coletta (JP Morgan AI Research, Italy); Flavio Giorgi, Gaia Maselli, Matteo Prata and Domenicomichele Silvestri (Sapienza University of Rome, Italy); Jonathan Ashdown (United States Air Force, USA); Francesco Restuccia (Northeastern University, USA)
Speaker Matteo Prata (Sapienza University of Rome, Italy)
Matteo Prata is a PhD student in the Department of Computer Science at Sapienza University of Rome, Italy. He has authored numerous research papers in the field of computer network performance, with a particular focus on unmanned aerial vehicle networks. Additionally, his research interests encompass AI applications in finance.
WiSwarm: Age-of-Information-based Wireless Networking for Collaborative Teams of UAVs
Vishrant Tripathi (MIT, USA); Igor Kadota (Columbia University, USA); Ezra Tal (MIT, USA); Muhammad Shahir Abdurrahman (Stanford University & Massachusetts Institute of Technology, USA); Alexander Warren, Sertac Karaman and Eytan Modiano (MIT, USA)
Speaker Vishrant Tripathi (MIT)
Vishrant Tripathi is a Ph.D. candidate in the EECS department at MIT, working with Prof. Eytan Modiano at the Laboratory for Information and Decision Systems (LIDS). His research is on modeling, analysis and design of communication networks, with emphasis on wireless and real-time networks. His current focus is on scheduling problems in networked control systems, multi-agent robotics and federated learning.
FlyTracker: Motion Tracking and Obstacle Detection for Drones Using Event Cameras
Yue Wu, Jingao Xu and Danyang Li (Tsinghua University, China); Yadong Xie (Beijing Institute of Technology, China); Hao Cao (Tsinghua University, China); Fan Li (Beijing Institute of Technology, China); Zheng Yang (Tsinghua University, China)
Speaker Yue Wu
Yue Wu received the doctor degree in Computer Science and Technology from Beijing Institute of Technology, in 2021. Currently she is a post-doctoral in the School of Software, Tsinghua University, Beijing, China. Her research interests include visual localization, mobile computing, and Internet of things.
Optical and Mobile
AGO: Boost Mobile AI Inference Performance by Removing Constraints on Graph Optimization
Zhiying Xu, Hongding Peng and Wei Wang (Nanjing University, China)
Speaker Zhiying Xu (Nanjing University)
I am a PhD candidate at Nanjing University, China. I am interested in machine learning system, compilation, and code generation techniques.
OpticNet: Self-Adjusting Networks for ToR-Matching-ToR Optical Switching Architectures
Caio Alves Caldeira (Universidade Federal de Minas Gerais, Brazil); Otavio Augusto de Oliveira Souza and Olga Goussevskaia (UFMG, Brazil); Stefan Schmid (University of Vienna, Austria)
In this work we propose a scalable matching model for scenarios where OCS have a constant number of ports. Furthermore, we present OpticNet, a framework that maps a set of $n$ static ToR switches to a set of $p$-port OCS to form any constant-degree topology. We prove that OpticNet uses a minimal number of reconfigurable switches to realize any desired network topology and allows to apply any existing self-adjusting network (SAN) algorithm on top of it, also preserving amortized performance guarantees. Our experimental results based on real workloads show that OpticNet is a flexible and efficient framework to design efficient SANs.
Speaker Otávio Augusto de Oliveira Souza (Universidade Federal of Minas Gerais)
Otávio A. de O. Souza received the M.Sc degree in Computer Science in 2020 from Universidade Federal de Minas Gerais (UFMG), Brazil, where he is currently a Ph.D. candidate in Computer Science. His research interest includes modeling, algorithm design, and analysis in communication networks, with emphasis on distributed systems.
An End-to-end Learning Framework for Joint Compensation of Impairments in Coherent Optical Communication Systems
Rui Zhang (University of Electronic Science and Technology of China, China); Min Liao and Jun Chen (Huawei Chengdu Research Center, China); Xusong Ning, Lin Li and Qinli Yang (University of Electronic Science and Technology of China, China); Yongsheng Xu (Huawei Chengdu Research Center, China); Junming Shao (University of Electronic Science and Technology of China, China)
Speaker Rui Zhang( University of Electronic Science and Technology of China)
I am a Ph.D. candidate at the School of Computer Science of the USETC under the supervision of Prof. Junimg Shao. My main research area is adversarial machine learning and its application with a particular focus on adversarial defense and the deep learning model's robustness.
Minimizing Age of Information for Underwater Optical Wireless Sensor Networks
Yu Tian, Lei Wang, Chi Lin, Yang Chi, Bingxian Lu and Zhenquan Qin (Dalian University of Technology, China)
Speaker Yu Tian (Dalian University of Technology)
Yu Tian received an M.S. degree from Inner Mongolia University, Hohhot, China, in 2019. He is currently pursuing a Ph.D. degree in software engineering from the Dalian University of Technology, Dalian, China. His research interest focuses on the underwater optical wireless network.
Flowrest: Practical Flow-Level Inference in Programmable Switches with Random Forests
Aristide Tanyi-Jong Akem (IMDEA Networks Institute, Spain & Universidad Carlos III de Madrid, Spain); Michele Gucciardo and Marco Fiore (IMDEA Networks Institute, Spain)
Speaker Aristide Tanyi-Jong Akem (IMDEA Networks Institute & Universidad Carlos III de Madrid)
Akem is a PhD student in the Networks Data Science Group at IMDEA Networks Institute in Madrid, Spain. He is also a student at Universidad Carlos III de Madrid, where he is enrolled in the Telematics Engineering program. Prior to his PhD studies, he completed an engineering degree at the University of Yaounde I, in Cameroon and a master's in electrical and computer engineering at Carnegie Mellon University Africa, in Rwanda. He is currently involved with the European Union's Horizon 2020 project "BANYAN" which aims to bring big data analytics to radio access networks. At the moment, he is visiting Orange Labs in Paris, France as part of the secondments of the project. Akem's current research interest is in the area of in-band network intelligence, with a focus on in-network machine learning.
Melody: Toward Resource-Efficient Packet Header Vector Encoding on Programmable Switches
Xiang Chen and Hongyan Liu (Zhejiang University, China); Qingjiang Xiao and Jianshan Zhang (Fuzhou University, China); Qun Huang (Peking University, China); Dong Zhang (Fuzhou University, China); Xuan Liu (Yangzhou University & Southeast University, China); Chunming Wu (College of Computer Science, Zhejiang University, China)
Speaker Xiang Chen
Xiang is a first-year PhD student at Zhejiang University. His advisors are Prof. Chunming Wu, Prof. Qun Huang, and Prof. Dong Zhang. He has received a Best Paper Award from IEEE/ACM IWQoS 2021 and a Best Paper Candidate from IEEE INFOCOM 2021. His research interests include programmable networks, network virtualization, and network security.
CLIP: Accelerating Features Deployment for Programmable Switch
Tingting Xu, Xiaoliang Wang and Chen Tian (Nanjing University, China); Yun Xiong and Yun Lin (HUAWEI, China); Baoliu Ye (Nanjing University, China)
Speaker Tingting Xu (Nanjing University)
Tingting Xu received the B.E. degree in 2019 from the college of Computer Science and Electronic Engineering, Hunan University, Hunan, China. She is currently working toward the Ph.D. degree in the Department of Computer Science and Technology, Nanjing University under the supervision of Prof.Xiaoliang Wang. Her research interests include programmable network, datacenter network, and network function virtulization.
RED: Distributed Program Deployment for Resource-aware Programmable Switches
Xingxin Jia, Fuliang Li and Songlin Chen (Northeastern University, China); Chengxi Gao (Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China); Pengfei Wang (Dalian University of Technology, China); Xingwei Wang (Northeastern University, China)
Speaker Xingxin Jia(Northeastern University, China)
Patrick P. C. Lee