Proceedings

Proceedings

Daniel Casini, Dakshina Dasari, and Matthias Becker (Eds.), Proceedings of the 1st Real-time And IntelliGent Edge Computing Workshop (RAGE 2022), San Francisco, California, USA, July 10th, 2022. [ ]

Papers & Slides

Opening Remarks [ ]
MArK8s - A Management Toolchain Approach for Automotive Real-Time Kubernetes Containers in the Mobile Edge Cloud [ ]
Bernhard Blieninger, Aaron Dietz and Uwe Baumgarten
Towards a Predictable and Cognitive Edge-Cloud Architecture for Industrial Systems [ ]
Mohammad Ashjaei, Saad Mubeen, Masoud Daneshtaalb, Victor Casamayor and Geoffrey Nelissen
RT-SCALER: Adaptive Resource Allocation Framework for Real-Time Containers [ ]
Vaclav Struhar, Silviu S. Craciunas, Mohammad Ashjaei, Moris Behnam and Alessandro Papadopoulos
Industrial use-cases for real-time edge-computing [ ]
Arne Hamann
High-performance real-time systems design from cloud to embedded edge [ ]
Matteo Andreozzi and Girish Shirasat
Priority-Driven Real-Time Scheduling in ROS2: Potential and Challenges [ ]
Hyunjong Choi, Daniel Enright, Hoora Sobhani, Yecheng Xiang and Hyoseung Kim
Priority-Driven Real-Time Scheduling in ROS2: Potential and Challenges [ ]
Hyunjong Choi, Daniel Enright, Hoora Sobhani, Yecheng Xiang and Hyoseung Kim
Giving the Software Defined Vehicle an Edge [ ]
Joerg Seitter
The role of virtualization at the edge for mixed-criticality applications [ ]
Giorgiomaria Cicero
zenoh: A Next-Generation Protocol for IoT and Edge Computing [ ]
Frédéric Desbiens
Minimal-Overlap Centrality-Driven Gateway Designation for Real-Time TSCH Networks [ ]
Miguel Gutiérrez Gaitán, Pedro d'Orey, Pedro Santos and Luís Almeida
No-more-unbounded-blocking queues: bounding transmission latencies in real-time edge computing [ ]
Gabriele Serra and Pietro Fara
Safety Verification of Third-Party Hardware Modules via Information Flow Tracking [ ]
Andres Meza, Francesco Restuccia, Ryan Kastner and Jason Oberg
Deadline-Aware Task Offloading for Vehicular Edge Computing Networks [ ]
Pratham Oza
Serving DNNs like Clockwork: Performance Predictability from the Bottom Up [ ]
Arpan Gujarati
QoS-aware resource management for Edge-AI [ ]
Hana Khamfroush
Low power Machine Learning Techniques for Edge-AI [ ]
Mohammad Al Faruque
Closing Remarks [ ]