We propose TTDeep, a deep reinforcement learning schedule framework, to incrementally schedule Time-Triggered (TT) flows and adapt to various topologies.
Comprehensive experiments show that. TTDeep can schedule TT flows much faster than solver-based methods and schedule nearly twice more TT flows on average.
Recent advancements in Reinforcement Learning (RL) have introduced scalable and adaptable solutions for industrial automation and dynamic task rescheduling ...
Apr 25, 2024 · TTDeep: Time-Triggered Scheduling for Real-Time Ethernet via Deep Reinforcement Learning. GLOBECOM 2021: 1-6. [c2]. view. electronic edition via ...
In this paper, we propose an algorithm called RLTS based on reinforcement learning and tree search, to optimize the end-to-end delays of both TT and RC messages ...
Missing: TTDeep: | Show results with:TTDeep:
... TTDeep: Time-Triggered Scheduling for Real-Time Ethernet via Deep Reinforcement Learning. ... Scheduling for Conflict-Free Network Updates in Time-Sensitive ...
May 14, 2024 · Zhao, “Ttdeep: Time-triggered scheduling for real-time ethernet via deep reinforcement learning,” Global Communications Conference, 2021.
In this paper, we propose an algorithm called RLTS based on reinforcement learning and tree search, to optimize the end-to-end delays of both TT and RC messages ...
Missing: TTDeep: | Show results with:TTDeep:
May 8, 2024 · Zhao, “Ttdeep: Time- triggered scheduling for real-time ethernet via deep reinforcement learn- ing,” Global Communications Conference, 2021.
Zhao, “Ttdeep: Time- triggered scheduling for real-time ethernet via deep reinforcement learn- ing,” in 2021 IEEE Global Communications Conference (GLOBECOM).