Venue of ACM SIGMETRICS 2023


Orlando, Florida, USA
June 19-22, 2023

Accepted Papers

Summer Deadline

  • Joint Learning and Control in Stochastic Queueing Networks with Unknown Utilities by Xinzhe Fu (MIT) and Eytan Modiano (MIT)
  • Characterizing Cryptocurrency-themed Malicious Browser Extensions by Kailong Wang (National University of Singapore), Yuxi Ling (National University of Singapore), Yanjun Zhang (Deakin University), Zhou Yu (Beijing University of Posts and Telecommunications), Haoyu Wang (Huazhong University of Science and Technology), Guangdong Bai (University of Queensland), Beng Chin Ooi (National University of Singapore), and Jin Song Dong (National University of Singapore)
  • Optimal Scheduling in the Multiserver-job Model under Heavy Traffic by Isaac Grosof (Carnegie Mellon University), Ziv Scully (Carnegie Mellon University), Alan Scheller-Wolf (Carnegie Mellon University), and Mor Harchol-Balter (Carnegie Mellon University)
  • Robust Multi-Agent Bandits Over Undirected Graphs by Daniel Vial (University of Texas at Austin), Sanjay Shakkottai (University of Texas, Austin), and R Srikant (UIUC)
  • The Online Knapsack Problem with Departures by Bo Sun (The Chinese University of Hong Kong), Lin Yang (The Chinese University of Hong Kong), Mohammad Hajiesmaili (University of Massachusetts Amherst), Adam Wierman (California Institute of Technology), John C. S. Lui (The Chinese University of Hong Kong), Don Towsley (University of Massachusetts - Amherst), and Danny H. K. Tsang (The Hong Kong University of Science and Technology)
  • Characterizing the Performance of Accelerated Edge Devices for Training Deep Learning Models by Prashanthi S.K (Indian Institute of Science), Sai Anuroop Kesanapalli (Indian Institute of Science), and Yogesh Simmhan (Indian Institute of Science)
  • On the stochastic and asymptotic improvement of First-Come First-Served and Nudge scheduling by Benny Van Houdt (University of Antwerp)
  • Leveraging the properties of mmWave Signals for 3D Finger Motion Tracking for Interactive IoT Applications by Yilin Liu (Penn State University), Shijia Zhang (Penn State University), Mahanth Gowda (Penn State University), and Srihari Nelakuditi (University of South Carolina)
  • Malcolm: Multi-agent Learning for Cooperative Load Management at Rack Scale by Ali Hossein Abbasi Abyaneh (University of Waterloo), Maizi Liao (University of Waterloo), and Seyed Majid Zahedi (University of Waterloo)
  • Dynamic Bin Packing with Predictions by Mozhengfu Liu (Nanyang Technological University), and Xueyan Tang (Nanyang Technological University)
  • Optimistic No-regret Algorithms for Discrete Caching by Naram Mhaisen (Delft University of Technology), Abhishek Sinha (Tata Institute of Fundamental Research), Georgios Paschos (Amazon), and Georgios Iosifidis (Delft University of Technology)
  • Streaming Algorithms for Constrained Submodular Maximization by Shuang Cui (University of Science and Technology of China), Kai Han (Soochow University), Jing Tang (The Hong Kong University of Science and Technology), He Huang (Soochow University), Xueying Li (Alibaba Group), and Zhiyu Li (Alibaba Group)
  • Funcipe: A Pipelined Serverless Framework for Fast and Cost-efficient Training of Deep Learning Models by Yunzhuo Liu (Shanghai Jiao Tong University), Bo Jiang (Shanghai Jiao Tong University), Tian Guo (Worcester Polytechnic Institute), Zimeng Huang (Shanghai Jiao Tong University), Wenhao Ma (Shanghai Jiao Tong University), Xinbing Wang (Shanghai Jiao Tong University), and Chenghu Zhou (Chinese Academy of Sciences)
  • Enabling Long-term Fairness in Dynamic Resource Allocation by Tareq Si Salem (Inria, Université Côte d'Azur), Georgios Iosifidis (Delft University of Technology), and Giovanni Neglia (Inria, Université Côte d'Azur)
  • Noise in the Clouds: Influence of Network Performance Variability on Application Scalability by Daniele De Sensi (ETH Zurich), Tiziano De Matteis (ETH Zurich), Konstantin Taranov (ETH Zurich), Salvatore Di Girolamo (ETH Zurich), Tobias Rahn (ETH Zurich), and Torsten Hoefler (ETH Zurich)
  • Switching in the Rain: Predictive Wireless x-haul Network Reconfiguration by Igor Kadota (Columbia University), Dror Jacoby (Tel Aviv University), Hagit Messer (Tel Aviv University), Gil Zussman (Columbia University), and Jonatan Ostrometzky (Tel Aviv University)
  • The M/M/k with deterministic setup times by Jalani K. Williams (Carnegie Mellon University), Mor Harchol-Balter (Carnegie Mellon University), and Weina Wang (Carnegie Mellon University)

Fall Deadline

  • DareShark: Detecting and Measuring Security Risks of Hosting-Based Dangling Domains by Mingming Zhang (Tsinghua University), Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), JianYu Lu (Qi An Xin Group Corp.), Yiming Zhang (Tsinghua University), Jianjun Chen (Tsinghua University), Haixin Duan (Institute for Network Science and Cyberspace, Tsinghua University; Qi An Xin Group Corp.), Shuang Hao (University of Texas at Dallas), and Xiaofeng Zheng (Institute for Network Sciences and Cyberspace, Tsinghua University; QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.)
  • Asynchronous Automata Processing on GPUs by Hongyuan Liu (William & Mary / The Hong Kong University of Science and Technology (Guangzhou)), Sreepathi Pai (University of Rochester), and Adwait Jog (William & Mary / University of Virginia)
  • DaeMon: Architectural Support for Efficient Data Movement in Fully Disaggregated Systems by Christina Giannoula (National Technical University of Athens), Kailong Huang (University of Toronto), Jonathan Tang (University of Toronto), Nectarios Koziris (National Technical University of Athens, Greece), Georgios Goumas (National Technical University of Athens), Zeshan Chishti (Intel Corporation), and Nandita Vijaykumar (University of Toronto)
  • Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes by Dongyan (Lucy) Huo (Cornell University), and Yudong Chen, Qiaomin Xie (University of Wisconsin-Madison)
  • Network Monitoring on Multi-Pipe Switches by Marco Chiesa (KTH Royal Institute of Technology) and Fábio L. Verdi (LERIS - UFSCar)
  • Power-of-d Choices Load Balancing in the Sub-Halfin Whitt Regime by Sushil Varma (Georgia Institute of Technology), Francisco Castro (University of California, Los Angeles), and Siva Theja Maguluri (Georgia Tech)
  • Detecting and Measuring Aggressive Location Harvesting in Mobile Apps via Data-flow Path Embedding by Haoran Lu (Indiana University Bloomington), Qingchuan Zhao (City University of Hong Kong), Yongliang Chen (City University of Hong Kong), Xiaojing Liao (Indiana University Bloomington), and Zhiqiang Lin (Ohio State University)
  • Gacha Game Analysis and Design by Canhui Chen (Tsinghua University) and Zhixuan Fang (Tsinghua Univerisity)
  • A Comparative Analysis of Ookla Speedtest and Measurement Labs Network Diagnostic Test (NDT7) by Kyle MacMillan (University of Chicago), Tarun Mangla (University of Chicago), James Saxon (University of Chicago), Nicole P. Marwell (University of Chicago), and Nick Feamster (University of Chicago)
  • Duo: A High-Throughput Reconfigurable Datacenter Network Using Local Routing and Control by Johannes Zerwas (Technische Universität München), Csaba Györgyi (ELTE Eötvös Loránd University, Budapest, Hungary), Andreas Blenk (Siemens AG), Stefan Schmid (TU Berlin), and Chen Avin (Ben Gurion University of the Negev)
  • (Private) Kernelized Bandits with Distributed Biased Feedback by Fengjiao Li (Virginia Tech), Xingyu Zhou (Wayne State University), and Bo Ji (Virginia Tech)
  • Fiat Lux: Illuminating IPv6 Apportionment with Different Datasets by Amanda Hsu (Georgia Institute of Technology), Frank Li (Georgia Institute of Technology), and Paul Pearce (Georgia Institute of Technology)
  • Batching of Tasks by Users of Pseudonymous Forums: Anonymity Compromise and Protection by Alexander Goldberg (Carnegie Mellon University), Giulia Fanti (Carnegie Mellon University), and Nihar Shah (Carnegie Mellon University)
  • Bias and Refinement of Multiscale Mean Field Models by Sebastian Allmeier (INRIA) and Nicolas Gast (INRIA)
  • PEACH: Proactive and Environment Aware Channel State Information Prediction with Depth Images by Serkut Ayvaşık (Technical University of Munich), Fidan Mehmeti (Technical University of Munich), Edwin Babaians (Technical University of Munich), and Wolfgang Kellerer (Technical University of Munich)
  • A First Look at Wi-Fi 6 in Action: Throughput, Latency, Energy Efficiency, and Security by Ruofeng Liu (Bosch Research) and Nakjung Choi (Ph.D., Network Systems and Security Research, Nokia Bell Labs)
  • Online Adversarial Stabilization of Unknown Networked Systems by Jing Yu (California Institute of Technology), Dimitar Ho (California Institute of Technology), and Adam Wierman (California Institute of Technology)
  • Each at its own pace: Third-party Dependency and Centralization Around the World by Rashna Kumar (Northwestern University), Sana Asif (Northwestern University), Elise Lee (Northwestern University), and Fabi'an E. Bustamante (Northwestern University)
  • SLITS: Sparsity-Lightened Intelligent Thread Scheduling by Wangkai Jin (Succincter) and Xiangjun Peng (Succincter)
  • Go-to-Controller is Better: Efficient and Optimal LPM Caching with Splicing by Itamar Gozlan (Ben-Gurion University of the Negev, Israel), Chen Avin (Ben-Gurion University of the Negev, Israel), Gil Einziger (Ben-Gurion University of the Negev, Israel), and Gabriel Scalosub (Ben-Gurion University of the Negev, Israel)
  • Mean-field Analysis for Load Balancing on Spatial Graphs by Daan Rutten (Georgia Institute of Technology) and Debankur Mukherjee (Georgia Institute of Technology)
  • Smoothed Online Optimization with Untrusted Predictions by Daan Rutten (Georgia Institute of Technology), Nicolas Christianson (California Institute of Technology), Debankur Mukherjee (Georgia Institute of Technology), and Adam Wierman (California Institute of Technology)
  • Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning by Yizhou Zhang (Tsinghua University), Guannan Qu (Carnegie Mellon University), Pan Xu (Duke University), Yiheng Lin (California Institute of Technology), Zaiwei Chen (California Institute of Technology), and Adam Wierman (California Institute of Technology)
  • JS Capsules: A Framework for Capturing Fine-grained JavaScript Memory Measurements for the Mobile Web by Usama Naseer (Brown University) and Theophilus A. Benson (Brown University and Carnegie Mellon University)
  • DiffForward: On Balancing Forwarding Traffic for Modern Cloud Block Services via Differentiated Forwarding by Wenzhe Zhu (University of Science and Technology of China), Yongkun Li (University of Science and Technology of China), Erci Xu (PDL), Fei Li (Alibaba Group), Yinlong Xu (University of Science and Technology of China), and John C. S. Lui (The Chinese University of Hong Kong)
  • Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks by Vamsi Addanki (TU Berlin), Chen Avin (Ben Gurion University of the Negev), and Stefan Schmid (TU Berlin)

Winter Deadline

  • SMASH: Flexible, Fast, and Resource-efficient Placement and Lookup of Distributed Storage by Yi Liu (University of California Santa Cruz), Shouqian Shi (University of California Santa Cruz), Minghao Xie (University of California Santa Cruz), Heiner Litz (University of California, Santa Cruz), and Chen Qian (University of California Santa Cruz)
  • Towards Accelerating Data Intensive Application's Shuffle Process Using SmartNICs by Jiaxin Lin (The University of Texas at Austin), Tao Ji (UT Austin), Xiangpeng Hao (UW Madison), Hokeun Cha (UW Madison), Yanfang Le (AMD), Xiangyao Yu (University of Wisconsin - Madison), and Aditya Akella (UT Austin)
  • Constant Regret Primal-Dual Policy for Multi-way Dynamic Matching by Yehua Wei (Duke University), Jiaming Xu (Duke University), and Sophie H. Yu (Duke University)
  • Online Fair Allocation with Perishable Resources by Sean R. Sinclair (Cornell University), Chamsi Hssaine (Amazon), and Siddhartha Banerjee (Cornell University)
  • Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure by Tyler Sam (Cornell University), Yudong Chen (University of Wisconsin-Madison), and Christina Lee Yu (Cornell University)
  • SplitRPC: A {Control + Data} Path Splitting RPC Stack for ML Inference Serving by Adithya Kumar (The Pennsylvania State University), Anand Sivasubramaniam (Penn State University), and Timothy Zhu (The Pennsylvania State University)
  • Online Resource Allocation under Horizon Uncertainty by Santiago Balseiro (Columbia University), Christian Kroer (Columbia University), and Rachitesh Kumar (Columbia University)
  • CoBF: Coordinated Beamforming in Dense mmWave Networks by Ding Zhang (George Mason University), Panneer Selvam Santhalingam (George Mason University), Parth Pathak (George Mason University), and Zizhan Zheng (Tulane University)
  • Real-time Spread Burst Detection in Data Streaming by Haibo Wang (University of Florida), Dimitrios Melissourgos (University of Florida), Chaoyi Ma (University of Florida), and Shigang Chen (University of Florida)
  • Strategic Latency Reduction in Blockchain Peer-to-Peer Networks by Weizhao Tang (CMU), Lucianna Kiffer (ETH Zurich), Giulia Fanti (CMU), and Ari Juels (Jacobs Institute, Cornell Tech)
  • Memtrade: Marketplace for Disaggregated Memory on Clouds by Hasan Al Maruf (University of Michigan),Yuhong Zhong (Columbia University), Hongyi Wang (Columbia University), Mosharaf Chowdhury (University of Michigan), Asaf Cidon (Columbia University), and Carl Waldspurger (Carl Waldspurger Consulting)