IEEE INFOCOM 2023
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 Chen Avin
Chen Avin is a Professor at the School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Israel. He received his MSc and Ph.D. in computer science from the University of California, Los Angeles (UCLA) in 2003 and 2006. Recently he served as the chair of the Communication Systems Engineering department at BGU. His current research interests are data-driven graphs and network algorithms, modeling, and analysis, emphasizing demand-aware networks, distributed systems, social networks, and randomized algorithms for networking.
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 Chenyang Xu (East China Normal University)
Chenyang Xu is now an assistant professor in East China Normal University. His research interests are broadly in operations research and theoretical computer science. His recent work mainly focuses on making use of machine learned predictions to design robust algorithms for combinatorial optimization problems, and some fair allocation topics.
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 Junhao Huang (Huazhong University of Science and Technology)
Junhao Huang received the B.S. degrees from the School of Computer Science and Engineering, Northeastern University, Shenyang, China, in 2020. He is currently pursuing the M.S. degree in the School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China . His current research interests mainly focus on cloud computing, and edge computing.
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 Peng Wang (Xidian University)
Peng is currently a Ph.D. student in Xidian University in Communication and Information System under the guidance of Prof. Hongyan Li (2018.9 ~ now) . He obtained his Bachelor from Xidian University in Telecommunications Engineering (2013.8~2017.6). He is also a Visiting Ph.D. student in Singapore University of Technology and Design under the guidance of Prof. Binbin Chen (2021.5~2022.11).
Peng's research mainly focuses on using graph theory, combination optimization and other mathematical tools to help model time-varying resources, analyze network capacity under different resource/QoS constraints and design delay-guaranteed routing and scheduling algorithms over the satellite and 5G terrestrial networks.
Neural Constrained Combinatorial Bandits
Shangshang Wang, Simeng Bian, Xin Liu and Ziyu Shao (ShanghaiTech University, China)
Speaker Shangshang Wang (ShanghaiTech University)
Shangshang Wang is currently a Master student in ShanghaiTech University under the guidance of Prof. Ziyu Shao in the Laboratory for Intelligence Information and Decision (2021 ~ now, majored in Computer Science). He obtained his Bachelor from ShanghaiTech University in Computer Science (2017 ~ 2021).
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 Jinhang Zuo (UMass Amherst & Caltech)
Jinhang Zuo is a joint postdoc at UMass Amherst and Caltech. He received his Ph.D. in ECE from CMU in 2022. His main research interests include online learning, resource allocation, and networked systems. He was a recipient of the CDS Postdoctoral Fellowship from UMass Amherst, Qualcomm Innovation Fellowship Finalist, AAAI-20 Student Scholarship, and Carnegie Institute of Technology Dean’s Fellowship.
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 Vishakha Ramani (Rutgers University)
Vishakha Ramani is a doctoral candidate at Rutgers University, where she is affiliated with the Wireless Information Networks Laboratory (WINLAB) and the Department of Electrical and Computer Engineering (ECE). In 2020, she earned a Master of Science degree from the ECE department at Rutgers University. Her research focuses on developing, analyzing, and designing algorithms for real-time networked systems, with a particular emphasis on using the Age-of-Information (AoI) as a performance metric of interest.
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 Tolga Atalay (Virginia Tech)
Tolga is a PhD Student at the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His work revolves around the system design and implementation of robust and scalable cybersecurity platforms for 5G/beyond networks.
A Close Look at 5G in the Wild: Unrealized Potentials and Implications
Yanbing Liu and Chunyi Peng (Purdue University, USA)
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 Paniz Parastar
Paniz Parastar is a PhD candidate in the Department of Informatics at the University of Oslo, Norway. She is a passionate networking researcher with expertise in network data analysis and optimization. During her PhD, she has been analyzing the real-world network to gain insights into the new use cases emerging in the 5G era. Currently, her focus is on connected cars, where she is investigating the requirements for deploying edge servers to enhance their performance.
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 Kaixuan Gao (Harbin Engineering University)
Kaixuan Gao received his B.E. degree in Computer Science and Technology in 2018. He is currently pursuing a PhD degree at Harbin Engineering University (HEU). His current research interests include high-precision localization, integrated sensing and communication (ISAC), AI, and future XG networks.