IEEE INFOCOM 2023
Opening, Awards, and Keynote
Opening, Awards, and Keynote
Nariman Farvardin (Stevens Institute of Technology, USA), Min Song (Stevens Institute of Technology, USA), Yusheng Ji (National Institute of Informatics, Japan) Yanchao Zhang (Arizona State University, USA), Gil Zussman (Columbia University, USA)
Speaker
Keynote Talk
Ion Stoica (University of California Berkeley, USA)
Speaker Ion Stoica (University of California Berkeley, USA)
Ion Stoica is a Professor in the EECS Department at the University of California at Berkeley, The Xu Bao Chancellor's Chair, and the Director of Sky Computing Lab (https://sky.cs.berkeley.edu). He is currently doing research on cloud computing and AI systems. Past work includes Apache Spark, Apache Mesos, Tachyon, Chord DHT, and Dynamic Packet State (DPS). He is an ACM Fellow, Honorary Member of the Romanian Academy of Sciences, and has received numerous awards, including the Mark Weiser Award (2019), SIGOPS Hall of Fame Award (2015), and several “Test of Time” awards. He also co-founded three companies, Anyscale (2019), Databricks (2013) and Conviva (2006).
Coffee Break
Cloud/Edge Computing 1
Balancing Repair Bandwidth and Sub-packetization in Erasure-Coded Storage via Elastic Transformation
Kaicheng Tang, Keyun Cheng and Helen H. W. Chan (The Chinese University of Hong Kong, Hong Kong); Xiaolu Li (Huazhong University of Science and Technology, China); Patrick Pak-Ching Lee (The Chinese University of Hong Kong, Hong Kong); Yuchong Hu (Huazhong University of Science and Technology, China); Jie Li and Ting-Yi Wu (Huawei Technologies Co., Ltd., Hong Kong)
Speaker
On Efficient Zygote Container Planning toward Fast Function Startup in Serverless Edge Cloud
Yuepeng Li and Deze Zeng (China University of Geosciences, China); Lin Gu (Huazhong University of Science and Technology, China); Mingwei Ou (China University of Geosciences(wuhan) & China University of Geosciences, China); Quan Chen (Shanghai Jiao Tong University, China)
Speaker
Layered Structure Aware Dependent Microservice Placement Toward Cost Efficient Edge Clouds
Deze Zeng (China University of Geosciences, China); Hongmin Geng (China University of Geosciences, Wuhan, China); Lin Gu (Huazhong University of Science and Technology, China); Zhexiong Li (University of Geosciences, China)
cloud. Fortunately, Docker, as the most widely used container, provides a unique layered architecture that allows the same layer to be shared between microservices so as to lower the deployment cost. Meanwhile, it is highly desirable to deploy dependent microservices of an application together to lower the operation cost. Therefore, the balancing of microservice deployment cost and the operation cost should be considered comprehensively to achieve minimal overall cost of an on-demand application. In this paper, we first formulate this problem into a Quadratic Integer Programming form (QIP) and prove it as a NP-hard problem. We further propose a Randomized Rounding-based Microservice Deployment and Layer Pulling (RR-MDLP) algorithm with low computation complexity and guaranteed approximation ratio. Through extensive experiments, we verify the high efficiency of our algorithm by the fact that it significantly outperforms existing state-of-the-art microservice deployment strategies.
Speaker
How to Attack and Congest Delay-Sensitive Applications on the Cloud
Jhonatan Tavori (Tel-Aviv University, Israel); Hanoch Levy (Tel Aviv University, Israel)
Speaker
Session Chair
Bo Ji
Federated Learning 1
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning
Yunming Liao (University of Science and Technology of China, China); Yang Xu (University of Science and Technology of China & School of Computer Science and Technology, China); Hongli Xu and Lun Wang (University of Science and Technology of China, China); Chen Qian (University of California at Santa Cruz, USA)
Speaker
Toward Sustainable AI: Federated Learning Demand Response in Cloud-Edge Systems via Auctions
Fei Wang (Beijing University of Posts and Telecommunications, China); Lei Jiao (University of Oregon, USA); Konglin Zhu (Beijing University of Posts and Telecommunications, China); Xiaojun Lin (Purdue University, USA); Lei Li (Beijing University of Posts And Telecommunications, China)
Speaker
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization
Heting Liu, Fang He and Guohong Cao (The Pennsylvania State University, USA)
Speaker
Asynchronous Federated Unlearning
Ningxin Su and Baochun Li (University of Toronto, Canada)
In this paper, we present the design and implementation of Knot, a new clustered aggregation mechanism custom-tailored to asynchronous federated learning. The design of Knot is based upon our intuition that client aggregation can be performed within each cluster only so that retraining due to data erasure can be limited to within each cluster as well. To optimize client-cluster assignment, we formulated a lexicographical minimization problem that could be transformed into a linear programming problem and solved efficiently. Over a variety of datasets and tasks, we have shown clear evidence that Knot outperformed the state-of-the-art federated unlearning mechanisms by up to 85% in the context of asynchronous federated learning.
Speaker Ningxin Su (University of Toronto)
Ningxin Su is a third-year Ph.D. student in the Department of Electrical and Computer Engineering, University of Toronto, under the supervision of Prof. Baochun Li. She received her M.E. and B.E. degrees from the University of Sheffield and Beijing University of Posts and Telecommunications in 2020 and 2019, respectively. Her research area includes distributed machine learning, federated learning and networking. Her website is located at ningxinsu.github.io.
Session Chair
Giovanni NEGLIA
LoRa and LPWAN
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
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.
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
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
Session Chair
Zhi Sun
mmWave 1
Rotation Speed Sensing with mmWave Radar
Rong Ding, Haiming Jin and Dingman Shen (Shanghai Jiao Tong University, China)
Speaker
mmEavesdropper: Signal Augmentation-based Directional Eavesdropping with mmWave Radar
Yiwen Feng, Kai Zhang, Chuyu Wang, Lei Xie, Jingyi Ning and Shijia Chen (Nanjing University, China)
Speaker
mmMIC: Multi-modal Speech Recognition based on mmWave Radar
Long Fan, Lei Xie, Xinran Lu, Yi Li, Chuyu Wang and Sanglu Lu (Nanjing University, China)
Speaker
Universal Targeted Adversarial Attacks Against mmWave-based Human Activity Recognition
Yucheng Xie (Indiana University-Purdue University Indianapolis, USA); Ruizhe Jiang (IUPUI, USA); Xiaonan Guo (George Mason University, USA); Yan Wang (Temple University, USA); Jerry Cheng (New York Institute of Technology, USA); Yingying Chen (Rutgers University, USA)
Speaker
Session Chair
Igor Kadota
Video Streaming 1
Buffer Awareness Neural Adaptive Video Streaming for Avoiding Extra Buffer Consumption
Tianchi Huang (Tsinghua University, China); Chao Zhou (Beijing Kuaishou Technology Co., Ltd, China); Rui-Xiao Zhang, Chenglei Wu and Lifeng Sun (Tsinghua University, China)
Speaker
From Ember to Blaze: Swift Interactive Video Adaptation via Meta-Reinforcement Learning
Xuedou Xiao, Mingxuan Yan and Yingying Zuo (Huazhong University of Science and Technology, China); Boxi Liu and Paul Ruan (Tencent Technology Co. Ltd, China); Yang Cao and Wei Wang (Huazhong University of Science and Technology, China)
Speaker
RDladder: Resolution-Duration Ladder for VBR-encoded Videos via Imitation Learning
Lianchen Jia (Tsinghua University, China); Chao Zhou (Beijing Kuaishou Technology Co., Ltd, China); Tianchi Huang, Chaoyang Li and Lifeng Sun (Tsinghua University, China)
Speaker
Energy-Efficient 360-Degree Video Streaming on Multicore-Based Mobile Devices
Xianda Chen and Guohong Cao (The Pennsylvania State University, USA)
Speaker
Datacenter and Switches
Dynamic Demand-Aware Link Scheduling for Reconfigurable Datacenters
Kathrin Hanauer, Monika Henzinger, Lara Ost and Stefan Schmid (University of Vienna, Austria)
This paper proposes a dynamic algorithms approach to improve the performance of reconfigurable datacenter networks, by supporting faster reactions to changes in the traffic demand. This approach leverages the temporal locality of traffic patterns in order to update the interconnecting matchings incrementally, rather than recomputing them from scratch. In particular, we present six (batch-)dynamic algorithms and compare them to static ones. We conduct an extensive empirical evaluation on 176 synthetic and 39 real-world traces, and find that dynamic algorithms can both significantly improve the running time and reduce the number of changes to the configuration, especially in networks with high temporal locality, while retaining matching quality.
Speaker
Scalable Real-Time Bandwidth Fairness in Switches
Robert MacDavid, Xiaoqi Chen and Jennifer Rexford (Princeton University, USA)
We propose Approximate Hierarchical Allocation of Bandwidth (AHAB), a per-user bandwidth limit enforcer that runs fully in the data plane of commodity switches. AHAB tracks each user's approximate traffic rate and compares it against a bandwidth limit, which is iteratively updated via a real-time feedback loop to achieve max-min fairness across users. Using a novel sketch data structure, AHAB avoids storing per-user state, and therefore scales to thousands of slices and millions of users. Furthermore, AHAB supports network slicing, where each slice has a guaranteed share of the bandwidth that can be scavenged by other slices when under-utilized. Evaluation shows AHAB can achieve fair bandwidth allocation within 3.1ms, 13x faster than prior data-plane hierarchical schedulers.
Speaker
Protean: Adaptive Management of Shared-Memory in Datacenter Switches
Hamidreza Almasi, Rohan Vardekar and Balajee Vamanan (University of Illinois at Chicago, USA)
periods of time. We implemented Protean in today's programmable switches and demonstrate their high performance with negligible overhead. Our at-scale ns-3 simulations show that Protean
reduces the tail latency by a factor of 5 over DT on average across varying loads with realistic workloads.
Speaker
Designing Optimal Compact Oblivious Routing for Datacenter Networks in Polynomial Time
Kanatip Chitavisutthivong (Vidyasirimedhi Institute of Science and Technology, Thailand); Chakchai So-In (Khon Kaen University, Thailand); Sucha Supittayapornpong (Vidyasirimedhi Institute of Science and Technology, Thailand)
Speaker
Theory 1
LOPO: An Out-of-order Layer Pulling Orchestration Strategy for Fast Microservice Startup
Lin Gu and Junhao Huang (Huazhong University of Science and Technology, China); Shaoxing Huang (Huazhong University of Science and Technology & HUST, China); Deze Zeng (China University of Geosciences, China); Bo Li (Hong Kong University of Science and Technology, Hong Kong); Hai Jin (Huazhong University of Science and Technology, China)
Speaker
Self-Adjusting Partially Ordered Lists
Vamsi Addanki (TU Berlin, Germany); Maciej Pacut (Technical University of Berlin, Germany); Arash Pourdamghani (TU Berlin, Germany); Gábor Rétvári (Budapest University of Technology and Economics, Hungary); Stefan Schmid and Juan Vanerio (University of Vienna, Austria)
Speaker Arash Pourdamghani (TU Berlin)
Arash Pourdamghani is a direct Ph.D. student at the INET group at the Technical University of Berlin, Germany. Previously he was a researcher at the University of Vienna and completed research internships at IST Austria and CUHK. He got his B.Sc. from the Sharif University of Technology. He is interested in algorithm design and analysis with applications in networks, distributed systems, and blockchains. His particular focus is on self-adjusting networks.
Online Dynamic Acknowledgement with Learned Predictions
Sungjin Im (University of California at Merced, USA); Benjamin Moseley (Carnegie Mellon University, USA); Chenyang Xu (East China Normal University, China); Ruilong Zhang (City University of Hong Kong, Hong Kong)
We develop algorithms that perform arbitrarily close to the optimum with accurate predictions while concurrently having the guarantees arbitrarily close to what the best online algorithms can offer without access to predictions, thereby achieving simultaneous optimum consistency and robustness. This new result is enabled by our novel prediction error measure. No error measure was defined for the problem prior to our work, and natural measures failed due to the challenge that requests with different arrival times have different effects on the objective. We hope our ideas can be used for other online problems with temporal aspects that have been resisting proper error measures.
Speaker
SeedTree: A Dynamically Optimal and Local Self-Adjusting Tree
Arash Pourdamghani (TU Berlin, Germany); Chen Avin (Ben-Gurion University of the Negev, Israel); Robert Sama and Stefan Schmid (University of Vienna, Austria)
Speaker Arash Pourdamghani (TU Berlin)
Arash Pourdamghani is a direct Ph.D. student at the INET group at the Technical University of Berlin, Germany. Previously he was a researcher at the University of Vienna and completed research internships at IST Austria and CUHK. He got his B.Sc. from the Sharif University of Technology. He is interested in algorithm design and analysis with applications in networks, distributed systems, and blockchains. His particular focus is on self-adjusting networks.
Session Chair
Xiaowen Gong
Conference Lunch
Wireless/Mobile Learning
Opportunistic Collaborative Estimation for Vehicular Systems
Saadallah Kassir and Gustavo de Veciana (The University of Texas at Austin, USA)
As vehicles might have different sensing capabilities, combining and sharing information from a judiciously selected subset is often sufficient to considerably improve all the vehicles' estimation errors.
We develop an opportunistic framework for vehicular collaborative sensing determining (1) which nodes require assistance, (2) which ones are best suited to provide it, and (3) the corresponding information-sharing rates, so as to minimize the communication overheads while meeting the vehicles' target estimation error. We leverage the supermodularity of the problem to devise an efficient vehicle information sharing algorithm with suboptimality guarantees to solve this problem and make it suitable to deploy in dynamic environments where network conditions might fluctuate rapidly. We support our analysis with simulations showing evidence that vehicles can considerably benefit from the proposed opportunistic collaborative sensing framework compared to operating autonomously. Finally, we explore the value of information-sharing in vehicular collaborative sensing networks by evaluating the associated safe driving velocity gains.
Speaker
Online Learning for Adaptive Probing and Scheduling in Dense WLANs
Tianyi Xu (Tulane University, USA); Ding Zhang (George Mason University, USA); Zizhan Zheng (Tulane University, USA)
Speaker
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN
Hongkuan Zhou (University of Southern California, USA); Rajgopal Kannan (US Army Research Lab, USA); Ananthram Swami (DEVCOM Army Research Laboratory, USA); Viktor K. Prasanna (University of Southern California, USA)
Speaker
FEAT: Towards Fast Environment-Adaptive Task Offloading and Power Allocation in MEC
Tao Ren (Institute of Software Chinese Academy of Sciences, China); Zheyuan Hu, Hang He, Jianwei Niu and Xuefeng Liu (Beihang University, China)
Speaker
Session Chair
Bin Li
Federated Learning 2
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression
Zhida Jiang (University of Science and Technology of China, China); Yang Xu (University of Science and Technology of China & School of Computer Science and Technology, China); Hongli Xu and Zhiyuan Wang (University of Science and Technology of China, China); Chen Qian (University of California at Santa Cruz, USA)
Speaker
FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection
Xiong Wang and Yuxin Chen (Huazhong University of Science and Technology, China); Yuqing Li (Wuhan University, China); Xiaofei Liao and Hai Jin (Huazhong University of Science and Technology, China); Bo Li (Hong Kong University of Science and Technology, Hong Kong)
Speaker
Federated Learning with Flexible Control
Shiqiang Wang (IBM T. J. Watson Research Center, USA); Jake Perazzone (US Army Research Lab, USA); Mingyue Ji (University of Utah, USA); Kevin S Chan (US Army Research Laboratory, USA)
Speaker Shiqiang Wang (IBM T. J. Watson Research Center, USA)
Shiqiang Wang is a Staff Research Scientist at IBM T. J. Watson Research Center, NY, USA. He received his Ph.D. from Imperial College London, United Kingdom, in 2015. His current research focuses on the intersection of distributed computing, machine learning, networking, and optimization, with a broad range of applications including data analytics, edge-based artificial intelligence (Edge AI), Internet of Things (IoT), and future wireless systems. He received the IEEE Communications Society (ComSoc) Leonard G. Abraham Prize in 2021, IEEE ComSoc Best Young Professional Award in Industry in 2021, IBM Outstanding Technical Achievement Awards (OTAA) in 2019, 2021, and 2022, multiple Invention Achievement Awards from IBM since 2016, Best Paper Finalist of the IEEE International Conference on Image Processing (ICIP) 2019, and Best Student Paper Award of the Network and Information Sciences International Technology Alliance (NIS-ITA) in 2015.
Federated Learning under Heterogeneous and Correlated Client Availability
Angelo Rodio (Inria, France); Francescomaria Faticanti (INRIA, France); Othmane Marfoq (Inria, France & Accenture Technology Labs, France); Giovanni Neglia (Inria, France); Emilio Leonardi (Politecnico di Torino, Italy)
Our experimental results show that CA-Fed has higher time-average accuracy and a lower standard deviation than state-of-the-art AdaFed and F3AST.
Speaker
Session Chair
Sajal K. Das
Satellite/Space Networking
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
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
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
SaTCP: Link-Layer Informed TCP Adaptation for Highly Dynamic LEO Satellite Networks
Xuyang Cao and Xinyu Zhang (University of California San Diego, USA)
Speaker
mmWave 2
Realizing Uplink MU-MIMO Communication in mmWave WLANs: Bayesian Optimization and Asynchronous Transmission
Shichen Zhang (Michigan State University, USA); Bo Ji (Virginia Tech, USA); Kai Zeng (George Mason University, USA); Huacheng Zeng (Michigan State University, USA)
Speaker
mmFlexible: Flexible Directional Frequency Multiplexing for Multi-user mmWave Networks
Ish Kumar Jain, Rohith Reddy Vennam and Raghav Subbaraman (University of California San Diego, USA); Dinesh Bharadia (University of California, San Diego, USA)
Speaker
On the Effective Capacity of RIS-enabled mmWave Networks with Outdated CSI
Syed Waqas Haider Shah (IMDEA Networks Institute, Spain & Information Technology University, Pakistan); Sai Pavan Deram and Joerg Widmer (IMDEA Networks Institute, Spain)
outdated CSI, which provides paradigmatic system performance, is difficult. To this end, this work aims to provide practical insights into the tradeoff between the outdatedness of the CSI and the system performance by using the effective capacity as analytical tool. We consider a RIS-enabled mmWave downlink whereby the base station operates under statistical quality-of-service constraints. We find a closed-form expression for the effective capacity that incorporates the degree of optimism of packet scheduling and correlation strength between instantaneous and outdated CSI. Moreover, our analysis allows us to find optimal values of the signal-to-interference-plus-noise-ratio (SINR) distribution parameter and their impact on the effective capacity in different network scenarios. Simulation results demonstrate that better effective capacity can be achieved with suboptimal RIS configuration when the channel estimates are known to be outdated. It allows us to design system parameters that guarantee better performance while keeping the complexity and cost associated with channel estimation to a minimum.
Speaker
flexRLM: Flexible Radio Link Monitoring for Multi-User Downlink Millimeter-Wave Networks
Aleksandar Ichkov and Aron Schott (RWTH Aachen University, Germany); Petri Mähönen (RWTH Aachen University, Germany & Aalto University, Finland); Ljiljana Simić (RWTH Aachen University, Germany)
Speaker Aleksandar Ichkov (RWTH Aachen University)
Session Chair
Falko Dressler
Video Streaming 2
OmniSense: Towards Edge-Assisted Online Analytics for 360-Degree Videos
Miao Zhang (Simon Fraser University, Canada); Yifei Zhu (Shanghai Jiao Tong University, China); Linfeng Shen (Simon Fraser University, Canada); Fangxin Wang (The Chinese University of Hong Kong, Shenzhen, China); Jiangchuan Liu (Simon Fraser University, Canada)
Speaker
Meta Reinforcement Learning for Rate Adaptation
Abdelhak Bentaleb (Concordia University, Canada); May Lim (National University of Singapore, Singapore); Mehmet N Akcay and Ali C. Begen (Ozyegin University, Turkey); Roger Zimmermann (National University of Singapore, Singapore)
Speaker
Cross-Camera Inference on the Constrained Edge
Jingzong Li (City University of Hong Kong, Hong Kong); Libin Liu (Zhongguancun Laboratory, China); Hong Xu (The Chinese University of Hong Kong, Hong Kong); Shudeng Wu (Tsinghua University, China); Chun Xue (City University of Hong Kong, Hong Kong)
Speaker Jingzong Li (City University of Hong Kong)
AdaptSLAM: Edge-Assisted Adaptive SLAM with Resource Constraints via Uncertainty Minimization
Ying Chen (Duke University, USA); Hazer Inaltekin (Macquarie University, Australia); Maria Gorlatova (Duke University, USA)
Speaker
Memory/Cache Management 1
ISAC: In-Switch Approximate Cache for IoT Object Detection and Recognition
Wenquan Xu and Zijian Zhang (Tsinghua University, China); Haoyu Song (Futurewei Technologies, USA); Shuxin Liu, Yong Feng and Bin Liu (Tsinghua University, China)
Speaker
No-regret Caching for Partial-observation Regime
Zifan Jia (Institute of Information Engineering, University of Chinese Academy of Sciences, China); Qingsong Liu (Tsinghua University, China); Xiaoyan Gu (Institute of Information Engineering, Chinese Academy of Sciences, China); Jiang Zhou (Chinese Academy of Sciences, China); Feifei Dai (University of Chinese Academy of Sciences, China); Bo Li and Weiping Wang (Institute of Information Engineering, Chinese Academy of Sciences, China)
Speaker
CoLUE: Collaborative TCAM Update in SDN Switches
Ruyi Yao and Cong Luo (Fudan University, China); Hao Mei (Fudan University); Chuhao Chen (Fudan University, China); Wenjun Li (Harvard University, USA); Ying Wan (China Mobile (Suzhou) Software Technology Co., Ltd, China); Sen Liu (Fudan University, China); Bin Liu (Tsinghua University, China); Yang Xu (Fudan University, China)
Speaker
Scalable RDMA Transport with Efficient Connection Sharing
Jian Tang and Xiaoliang Wang (Nanjing University, China); Huichen Dai (Huawei, China); Huichen Dai (Tsinghua University, China)
Speaker
Session Chair
Stratis Ioannidis
Theory 2
One Pass is Sufficient: A Solver for Minimizing Data Delivery Time over Time-varying Networks
Peng Wang (Xidian University, China); Suman Sourav (Singapore University of Technology and Design, Singapore); Hongyan Li (Xidian University, China); Binbin Chen (Singapore University of Technology and Design, Singapore)
Speaker
Neural Constrained Combinatorial Bandits
Shangshang Wang, Simeng Bian, Xin Liu and Ziyu Shao (ShanghaiTech University, China)
Speaker
Variance-Adaptive Algorithm for Probabilistic Maximum Coverage Bandits with General Feedback
Xutong Liu (The Chinese University of Hong Kong, Hong Kong); Jinhang Zuo (Carnegie Mellon University, USA); Hong Xie (Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, China); Carlee Joe-Wong (Carnegie Mellon University, USA); John C.S. Lui (The Chinese University of Hong Kong, Hong Kong)
Speaker
Lock-based or Lock-less: Which Is Fresh?
Vishakha Ramani (Rutgers University, USA); Jiachen Chen (WINLAB, Rutgers University, USA); Roy Yates (Rutgers University, USA)
Speaker
Demo Session 1
Demo Abstract: Scaling Out srsRAN Through Interfacing Wirelessly srsENB With srsEPC
Neha Mishra, Yamini V Iyengar, Akshay C. Raikar, Nikitha Thomas and Sabarish Krishna Moorthy (University at Buffalo, USA); Jiangqi Hu (University of Buffalo, USA); Zhiyuan Zhao and Nicholas Mastronarde (University at Buffalo, USA); Elizabeth Serena Bentley (AFRL, USA); Michael Medley (US Air Force Research Laboratory/Information Directorate & SUNY Polytechnic Institute, USA); Zhangyu Guan (University at Buffalo, USA)
Speaker Jiangqi Hu; Zhangyu Guan
Accelerating BLE Neighbor Discovery via Wi-Fi Fingerprints
Tong Li, Bowen Hu, Guanjie Tu and Jinwen Shuai (Renmin University of China, China); Jiaxin Liang (Huawei Technologies, China); Yukuan Ding (Hong Kong University of Science and Technology, Hong Kong); Ziwei Li and Ke Xu (Tsinghua University, China)
Speaker
A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN
Farhad Rezazadeh (UPC & CTTC, Spain); Lanfranco Zanzi (NEC Laboratories Europe, Germany); Francesco Devoti (NEC Laboratories Europe GmbH, Germany); Sergio Barrachina-Muñoz (Centre Tecnològic Telecomunicacions Catalunya, Spain); Engin Zeydan (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain); Xavier Costa-Perez (ICREA and i2cat & NEC Laboratories Europe, Spain); Josep Mangues-Bafalluy (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain)
Speaker Sergio Barrachina-Muñoz
Enabling CBRS Experimentation through an Open SAS and SDR-based CBSD
Oren R Collaco (Commonwealth Cyber Initiative Virginia Tech, USA); Mayukh Roy Chowdhury (Virginia Tech, USA); Aloizio Pereira Da Silva (Virginia Tech, USA & Commonwealth Cyber Initiative, USA); Luiz DaSilva (Virginia Tech, USA & Trinity College Dublin, Ireland)
Speaker
RIC-O: An Orchestrator for the Dynamic Placement of a Disaggregated RAN Intelligent Controller
Gustavo Zanatta Bruno (UNISINOS, Brazil); Vikas Krishnan Radhakrishnan (Virginia Tech, USA); Gabriel Almeida (Universidade Federal de Goiás, Brazil); Alexandre Huff (Federal Technological University of Parana, Brazil); Aloizio Pereira Da Silva (Virginia Tech, USA & Commonwealth Cyber Initiative, USA); Kleber V Cardoso (Universidade Federal de Goiás, Brazil); Luiz DaSilva (Virginia Tech, USA & Trinity College Dublin, Ireland); Cristiano Bonato Both (Unisinos University, Brazil)
Speaker
Remote Detection of 4G/5G UEs Vulnerable to Stealthy Call DoS
Man-Hsin Chen, Chiung-I Wu, Yin-Chi Li and Chi-Yu Li (National Yang Ming Chiao Tung University, Taiwan); Guan-Hua Tu (Michigan State Unversity, USA)
Speaker Man-Hsin Chen
Demonstration of LAN-type Communication for an Industrial 5G Network
Linh-An Phan, Dirk Pesch, Utz Roedig and Cormac J. Sreenan (University College Cork, Ireland)
Speaker Linh-An Phan
OREOS: Demonstrating E2E Orchestration in 5G Networks with Open-Source Components
Noé Godinho (University of Coimbra, Portugal); Paulo Duarte and Paulo Martins (Capgemini Engineering, Portugal); David Perez Abreu (University of Coimbra, Portugal & Instituto Pedro Nunes, Portugal); Raul F. D. Barbosa (Universidade de Aveiro, Portugal & Capgemini, Portugal); Bruno Miguel Fonseca Mendes (University of Aveiro, Portugal); João Fonseca (Capgemini Engineering, Portugal); Marco Silva (University of Coimbra, Portugal); Marco Araujo and João Donato Silva (Capgemini Engineering, Portugal); Karima Velasquez, Bruno Miguel Sousa and Marilia Curado (University of Coimbra, Portugal); Adriano Almeida Goes (Capgemini Engineering, Portugal)
Speaker
400G Ethernet Packet Capture Demo Based on Network Development Kit for FPGAs
Jakub Cabal, Vladislav Válek, Martin Špinler and Daniel Kondys (CESNET, Czech Republic); Jan Korenek (Brno University of Technology & CESNET, Czech Republic)
Speaker
Critical Element First: Enhance C-V2X Signal Coverage using Power-Efficient Liquid Metal-Based Intelligent Reflective Surfaces
Saige J Dacuycuy (University of Hawaii at Manoa, USA); Zachary Dela Cruz (University of Hawaii, USA); Yanjun Pan (University of Arkansas, USA); Yao Zheng (University of Hawai'i at Mānoa, USA); Aaron T. Ohta (University of Hawaii, USA); Wayne A. Shiroma (University of Hawaii at Manoa, USA)
Speaker
Security and Privacy
Communication Efficient Secret Sharing with Dynamic Communication-Computation Conversion
Zhenghang Ren (Hong Kong University of Science and Technology, China); Xiaodian Cheng and Mingxuan Fan (Hong Kong University of Science and Technology, Hong Kong); Junxue Zhang (Hong Kong University of Science and Technology, China); Cheng Hong (Alibaba Group, China)
To reduce the communication overhead of SS, prior works statically convert interactive operations to equivalent non-interactive operations with extra computation cost. However, we show that such static conversion misses chances for optimization, and further present SOLAR, a SS-based MPC framework that aims to reduce the communication overhead through dynamic communication-computation conversion. At its heart, SOLAR converts interactive operations that involve communication among parties to equivalent non-interactive operations within each party with extra computations and introduces a speculative strategy to perform opportunistic conversion when CPU is idle for network transmission. We have implemented and evaluated SOLAR on several popular MPC applications, and achieved 1.6-8.1x speedup in multi-thread setting compared to the basic SS and 1.2-8.6x speedup over static conversion.
Speaker
Stateful Switch: Optimized Time Series Release with Local Differential Privacy
Qingqing Ye and Haibo Hu (Hong Kong Polytechnic University, Hong Kong); Kai Huang (The Hong Kong University of Science and Technology, Hong Kong); Man Ho Au (The University of Hong Kong & The Hong Kong Polytechnic University, Hong Kong); Qiao Xue (Hong Kong Polytechnic University, Hong Kong)
Speaker
Privacy-preserving Stable Crowdsensing Data Trading for Unknown Market
He Sun, Mingjun Xiao and Yin Xu (University of Science and Technology of China, China); Guoju Gao (Soochow University, China); Shu Zhang (University of Science and Technology of China, China)
Speaker
Privacy as a Resource in Differentially Private Federated Learning
Jinliang Yuan, Shangguang Wang and Shihe Wang (Beijing University of Posts and Telecommunications, China); Yuanchun Li (Tsinghua University, China); Xiao Ma (Beijing University of Posts and Telecommunications, China); Ao Zhou (Beijing University of Posts & Telecommunications, China); Mengwei Xu (Beijing University of Posts and Telecommunications, China)
Speaker
Session Chair
Wenhai Sun
Federated Learning 3
A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning
Yongheng Deng and Ju Ren (Tsinghua University, China); Cheng Tang and Feng Lyu (Central South University, China); Yang Liu and Yaoxue Zhang (Tsinghua University, China)
Speaker
Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis
Ming Tang (Southern University of Science and Technology, China); Vincent W.S. Wong (University of British Columbia, Canada)
Speaker
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning
Anran Li (Nanyang Technological University, Singapore); Hongyi Peng (Nanyang Technological University, Singapore & Alibaba Group, China); Lan Zhang and Jiahui Huang (University of Science and Technology of China, China); Qing Guo, Han Yu and Yang Liu (Nanyang Technological University, Singapore)
Speaker
Joint Participation Incentive and Network Pricing Design for Federated Learning
Ningning Ding (Northwestern University, USA); Lin Gao (Harbin Institute of Technology (Shenzhen), China); Jianwei Huang (The Chinese University of Hong Kong, Shenzhen, China)
Speaker
Session Chair
Danda B Rawat
Internet Routing
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
A Learning Approach to Minimum Delay Routing in Stochastic Queueing Networks
Xinzhe Fu (Massachusetts Institute of Technology, USA); Eytan Modiano (MIT, USA)
Speaker
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
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
mmWave 3
MIA: A Transport-Layer Plugin for Immersive Applications in Millimeter Wave Access Networks
Zongshen Wu (University of Wisconsin Madison, USA); Chin-Ya Huang (National Taiwan University of Science and Technology, Taiwan); Parmesh Ramanathan (WISC, France)
Speaker
High-speed Machine Learning-enhanced Receiver for Millimeter-Wave Systems
Dolores Garcia and Rafael Ruiz (Imdea Networks, Spain); Jesús O. Lacruz and Joerg Widmer (IMDEA Networks Institute, Spain)
Speaker
Argosleep: Monitoring Sleep Posture from Commodity Millimeter-Wave Devices
Aakriti Adhikari and Sanjib Sur (University of South Carolina, USA)
Speaker
Safehaul: Risk-Averse Learning for Reliable mmWave Self-Backhauling in 6G Networks
Amir Ashtari Gargari (University of Padova, Italy); Andrea Ortiz (TU Darmstadt, Germany); Matteo Pagin (University of Padua, Italy); Anja Klein (TU Darmstadt, Germany); Matthias Hollick (Technische Universität Darmstadt & Secure Mobile Networking Lab, Germany); Michele Zorzi (University of Padova, Italy); Arash Asadi (TU Darmstadt, Germany)
Speaker
Session Chair
Joerg Widmer
Video Streaming 3
Who is the Rising Star? Demystifying the Promising Streamers in Crowdsourced Live Streaming
Rui-Xiao Zhang, Tianchi Huang, Chenglei Wu and Lifeng Sun (Tsinghua University, China)
Speaker
StreamSwitch: Fulfilling Latency Service-Layer Agreement for Stateful Streaming
Zhaochen She, Yancan Mao, Hailin Xiang, Xin Wang and Richard T. B. Ma (National University of Singapore, Singapore)
Speaker
Latency-Oriented Elastic Memory Management at Task-Granularity for Stateful Streaming Processing
Rengan Dou and Richard T. B. Ma (National University of Singapore, Singapore)
Speaker
Hawkeye: A Dynamic and Stateless Multicast Mechanism with Deep Reinforcement Learning
Lie Lu (Tsinghua University, China); Qing Li and Dan Zhao (Peng Cheng Laboratory, China); Yuan Yang and Zeyu Luan (Tsinghua University, China); Jianer Zhou (SUSTech, China); Yong Jiang (Graduate School at Shenzhen, Tsinghua University, China); Mingwei Xu (Tsinghua University, China)
Speaker
Internet Measurement
FlowBench: A Flexible Flow Table Benchmark for Comprehensive Algorithm Evaluation
Zhikang Chen (Tsinghua University, China); Ying Wan (China Mobile (Suzhou) Software Technology Co., Ltd, China); Ting Zhang (Tsinghua University, China); Haoyu Song (Futurewei Technologies, USA); Bin Liu (Tsinghua University, China)
Speaker
DUNE: Improving Accuracy for Sketch-INT Network Measurement Systems
Zhongxiang Wei, Ye Tian, Wei Chen, Liyuan Gu and Xinming Zhang (University of Science and Technology of China, China)
Speaker Wei Chen(University of Science and Technology of China)
Wei Chen is a Ph.D student in the department of Computer Science and Technology, University of Science and Technology of China. He is supervised by Prof. Ye Tian. He received the bachelor’s degree in University of Science and Technology of China in 2020. His research interests include network measurement and management.
On Data Processing through the Lenses of S3 Object Lambda
Pablo Gimeno-Sarroca and Marc Sánchez Artigas (Universitat Rovira i Virgili, Spain)
Speaker Pablo Gimeno-Sarroca (Universitat Rovira i Virgili)
Search in the Expanse: Towards Active and Global IPv6 Hitlists
Bingnan Hou and Zhiping Cai (National University of Defense Technology, China); Kui Wu (University of Victoria, Canada); Tao Yang and Tongqing Zhou (National University of Defense Technology, China)
Speaker Bingnan Hou (National University of Defense Technology)
Bingnan Hou received the bachelor’s and master’s degrees in Network Engineering from Nanjing University of Science and Technology, China, in 2010 and 2015, respectively, and the Ph.D degree in Computer Science and Technology from National University of Defense Technology, China, in 2022. His research interests include network measurement and network security.
Session Chair
Chen Qian
5G
Your Locations May Be Lies: Selective-PRS-Spoofing Attacks and Defence on 5G NR Positioning Systems
Kaixuan Gao, Wang Huiqiang and Hongwu Lv (Harbin Engineering University, China); Pengfei Gao (China Unicom Heilongjiang Branch, China)
Speaker
A Close Look at 5G in the Wild: Unrealized Potentials and Implications
Yanbing Liu and Chunyi Peng (Purdue University, USA)
Speaker
Spotlight on 5G: Performance, Device Evolution and Challenges from a Mobile Operator Perspective
Paniz Parastar (University of Oslo, Norway); Andra Lutu (Telefónica Research, Spain); Ozgu Alay (University of Oslo & Simula Metropolitan, Norway); Giuseppe Caso (Ericsson Research, Sweden); Diego Perino (Meta, Spain)
In this paper, we conduct a large-scale measurement study of a commercial mobile operator in the UK, focusing on bringing forward a real-world view on the available network resources, as well as how more than 30M end-user devices utilize the mobile network. We focus on the current status of the 5G Non-Standalone (NSA) deployment and the network-level performance and show how it caters to the prominent use cases that 5G promises to support. Finally, we demonstrate that a fine-granular set of requirements is, in fact, necessary to orchestrate the service to the diverse groups of 5G devices, some of which operate in permanent roaming.
Speaker
Securing 5G OpenRAN with a Scalable Authorization Framework for xApps
Tolga O Atalay and Sudip Maitra (Virginia Tech, USA); Dragoslav Stojadinovic (Kryptowire LLC, USA); Angelos Stavrou (Virginia Tech & Kryptowire, USA); Haining Wang (Virginia Tech, USA)
Speaker
Chartered Cruise Dinner (for attendees with Full Conference Registrations)
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