AORTA: Advanced Offloading for Real-Time Applications
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We are currently witnessing a second wave of cloud services that go beyond web storefronts and IT systems, including the digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. AORTA aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambition is to support a future ecosystem around robotics that enables a new level of flexible productivity in the manufacturing industry. AORTA will develop technologies that allow offloading of real-time services and functionality to the edge and cloud. We will build upon recent advances in 5G and cloud and networking technologies, as well as cutting-edge research results. The AORTA framework will support a fluid compute model where functionality will be dynamically deployed locally, at the edge, or in the cloud and support integration and real-time performance irrespective of where they execute. The results of the project will be demonstrated in a real-world robotics building construction scenario running on a live 5G network with real-world edge and large-scale cloud service. The AORTA technologies will impact automation SMEs and system integrators by adding real-time capabilities needed to evolve beyond the currently closed ecosystem. They will also add value to telecom providers and operators that may host these new automation services in addition to their current portfolio.
| First Name | Last Name | Title |
|---|---|---|
| Hans | Hansson | Professor |
| Saad | Mubeen | Professor |
| Mohammad | Ashjaei | Associate Professor,Docent |
A Study of On-Device Deep Reinforcement Learning for Task Offloading under Dynamic 5G Channel Conditions (Sep 2025) Gorka Nieto , Idoia de la Iglesia , Unai LOPEZ , Cristina Perfecto , Mohammad Ashjaei, Ali Balador International Conference on Evaluation and Assessment in Software Engineering (ETFA'25)
Problem-Based Learning in an Educational and Training Module on Model-Based Development of Vehicle Software (Jun 2025) Saad Mubeen, Mohammad Ashjaei International Conference on Evaluation and Assessment in Software Engineering (EASE'25)
Deadline-constrained security-aware workflow scheduling in hybrid cloud architecture (Aug 2024) Somayeh Abdi, Mohammad Ashjaei, Saad Mubeen Future Generation Computer Systems (FGCS)
Cost-aware Workflow Offloading in Edge-Cloud Computing Using a Genetic Algorithm (Jul 2024) Somayeh Abdi, Saad Mubeen, Mohammad Ashjaei The Journal of Supercomputing (Supercomputing)
Server Time Reservation for Periodic Real-Time Applications (Dec 2023) Ali Balador, Lizzy Tengana , Mohammad Ashjaei, Saad Mubeen The First International Workshop on Intelligent Systems and Paradigms for Next Generation Computing Evolution (INSPIRE'23)
Timing Predictability and Performance Standoff in Component-based Vehicle Software on Multi-core (Mar 2023) Saad Mubeen IEEE International Conference on Software Architecture Companion Proceedings (MDE4SA@ICSA 2023)
