Program

Session chair: Duong Nguyen

1. A Data-driven Optimal Control decision-making System for Multiple Autonomous Vehicles. 
Liuwang Kang, Haiying Shen (University of Virginia)

2. FENXI: Deep-learning Traffic Analytics at the edge. 
Massimo Gallo, Alessandro Finamore, Gwendal Simon, Dario Rossi (Huawei)

3. The Benefit of the Doubt: Uncertainty Aware Sensing for Edge Computing Platforms. 
Lorena Qendro, Jagmohan Chauhan (University of Cambridge), Alberto Gil C. P. Ramos (Samsung AI Center Cambridge), Cecilia Mascolo (University of Cambridge)

Session chair: Haris Volos

1. ePulsar: Control Plane for Publish-Subscribe Systemson Geo-Distributed Edge Infrastructure. 
Harshit Gupta, Tyler C Landle, Umakishore Ramachandran (Georgia Institute of Technology)

2. OneOS: Middleware for Running Edge Computing Applications as Distributed POSIX Pipelines. 
Kumseok Jung (University of British Columbia), Julien Gascon-Samson (ÉTS Montréal), Karthik Pattabiraman (University of British Columbia)

3. Will They or Won’t They?: Toward Effective Prediction of Watch Behavior for Time-Shifted Edge-Caching of Netflix Series Videos. 
Shruti Lall, Raghupathy Sivakumar (Georgia Institute of Technology)

Session chair: Zheng Dong

1. The Performance Argument for Blockchain-based Edge DNS Caching. 
James Choncholas, Ketan Bhardwaj, Ada Gavrilovska (Georgia Tech)

2. Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications. 
Young D. Kwon (University of Cambridge), Jagmohan Chauhan (University of Southampton), Abhishek Kumar (University of Helsinki), Pan (Ben) Hui (HKUST), Cecilia Mascolo (University of Cambridge)

1.  Learning based edge computing in air-to-air communication network. 
Zhe Wang (University of Louisville), Hongxiang Li (University of Louisville), Eric. J. Knoblock (NASA), Rafael D. Apaza (NASA)

2.  Towards Open and Cross Domain Edge Emulation - The AdvantEDGE Platform. 
Robert Gazda (InterDigital), Michel Roy (InterDigital), Jim Blakley (Carnegie Mellon University), Aly Sakr (Dortmund University of Applied Sciences and Arts), Rolf Schuster (Dortmund University of Applied Sciences and Arts)

3.  Edge Intelligence for Beyond-5G through Federated Learning. 
Shashank Jere (Virginia Tech), Yang Yi (Virginia Tech)

1.  SquaFL: Sketch-Quantization Inspired Communication Efficient Federated Learning. 
Pavana Prakash (University of Houston), Jiahao Ding (University of Houston), Minglei Shu (Shandong Academy of Sciences, China), Junyi Wang (Guilin University of Electronic Technology, China), Wenjun Xu (Beijing University of Posts and Telecommunications), Miao Pan (University of Houston)

2.  Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing. 
Pinyarash Pinyoanuntapong (University of North Carolina at Charlotte), Tagore Pothuneedi (University of North Carolina at Charlotte), Ravikumar Balakrishnan (Intel), Minwoo Lee (University of North Carolina at Charlotte), Chen Chen (University of Central Florida), Pu Wang (University of North Carolina at Charlotte)

3.  Collaborative Cloud-Edge-Local Computation Offloading for Multi-Component Applications. 
Anousheh Gholami (University of Maryland, College Park), John S. Baras (University of Maryland, College Park)

1.  Federated Learning with Infrastructure Resource Limitations in Vehicular Object Detection. 
Yiyue Chen (The University of Texas at Austin), Chianing Wang (Toyota Motor North America), BaekGyu Kim (Toyota Motor North America)

2.  Edge-Assisted Cooperative Perception in Autonomous Driving: A Reflection on Communication Design.  
Ruozhou Yu (North Carolina State University), Dejun Yang (Colorado School of Mines), Hao Zhang (Colorado School of Mines)

3.  Spectrum-Aware Mobile Edge Computing for UAVs Using Reinforcement Learning.  
Babak Badnava (University of Kansas), Taejoon Kim (University of Kansas), Morteza Hashemi (University of Kansas)

1.  You can enjoy augmented reality while running around: An edge-based mobile AR system. 
Haoxin Wang (University of North Carolina at Charlotte), Jiang Xie (University of North Carolina at Charlotte)

2.  Edge-based Fever Screening System Over Private 5G.  
Murugan Sankaradas (NEC Laboratories America), Kunal Rao (NEC Laboratories America), Ravi K. Rajendran (NEC Laboratories America), Amit Redkar (NEC Laboratories America), Srimat Chakradhar (NEC Laboratories America)

3.  iBranchy: An Accelerated edge inference platform for IoT Devices.  
Santosh K. Nukavarapu (Virginia Common Wealth University), Mohammad Ayyat (Virginia Common Wealth University), Tamer Nadeem (Virginia Common Wealth University)

1.  Security and safety threat modeling in edge computing. 
Denzler (TU Vienna), Hollerer (TU Vienna), Fruehwirth (Austrian Center for Digital Production), Kastner (TU Vienna)

2.  Scheduling Real-Time Applications on Edge Computing Platforms with Remote Attestation for Security. 
Reusch (TU Denmark), Pop (TU Denmark)

3.  Industrial Edge-based Cyber-Physical Systems - application needs and concerns for realization. 
Toerngren (KTH Stockholm), Thompson (Thinkk), Herzog (SAAB), Inam (Ercisson), Gross (KTH Stockholm), Dán (KTH Stockholm)

1.  Data-Driven End-to-End Delay Violation Probability Prediction with Extreme Value Mixture Models. 
Mostafavi (KTH Stockholm), Dán (KTH Stockholm), Gross (KTH Stockholm)

2.  A Decomposed Deep Training Solution for Fog Computing Platforms. 
Qian (TU Denmark), Barzegaran (TU Denmark)

3.  Decentralized task offloading decision making in an adversarial environment. 
B. Cho, Y. Xiao (Aalto University)

1.  Adaptive Security Risk Mitigation in Edge Computing: Randomized Defense Meets Prospect Theory. 
Talal Halabi (University of Winnipeg)

2.  TrustZone Enhanced Plausibly Deniable Encryption System for Mobile Devices.  
Jinghui Liao (Wayne State University), Bo Chen (Michigan Technological University), Weisong Shi (Wayne State University)

3.  How BlockChain Can Help Enhance the Security and Privacy in Edge Computing?.  
Jinyue Song, Tianbo Gu, Prasant Mohapatra (University of California, Davis)

1.  CANGuard: Practical Intrusion Detection for In-Vehicle Network via Unsupervised Learning. 
Wu Zhou (DiDi Labs, California, USA), Hao Fu (Facebook), Shray Kapoor (DiDi Labs, California, USA)

2.  MailLeak: Obfuscation-Robust Character Extraction Using Transfer Learning.  
Wei Wang (University of Maryland Baltimore County) , Zeyu Ning (University of Maryland Baltimore County), Hugues Iradukunda (University of Maryland Baltimore County), Qingquan Zhang (University of Maryland Baltimore County, University of Illinois at Urbana-Champaign), Ting Zhu (University of Maryland Baltimore County), and Ping Yi (Shanghai Jiaotong University)