CPU frequency scheduling of real-time applications on embedded devices with temporal encoding-based deep reinforcement learning
Small devices are frequently used in IoT and smart-city applications to perform periodic
dedicated tasks with soft deadlines. This work focuses on developing methods to derive …
dedicated tasks with soft deadlines. This work focuses on developing methods to derive …
Chauffeur: Benchmark suite for design and end-to-end analysis of self-driving vehicles on embedded systems
Self-driving systems execute an ensemble of different self-driving workloads on embedded
systems in an end-to-end manner, subject to functional and performance requirements. To …
systems in an end-to-end manner, subject to functional and performance requirements. To …
EASYR: E nergy-Efficient A daptive Sy stem R econfiguration for Dynamic Deadlines in Autonomous Driving on Multicore Processors
The increasing computing demands of autonomous driving applications have driven the
adoption of multicore processors in real-time systems, which in turn renders energy …
adoption of multicore processors in real-time systems, which in turn renders energy …
Dynamic partitioned scheduling of real-time dag tasks on arm big. little architectures
A Mascitti, T Cucinotta - … of the 29th International Conference on Real …, 2021 - dl.acm.org
This paper evaluates the combination of a Directed Acyclic Graph (DAG) task splitting
technique already proposed in the literature and the state-of-the-art, energy-aware version …
technique already proposed in the literature and the state-of-the-art, energy-aware version …
Deadline-aware deep-recurrent-q-network governor for smart energy saving
Complex cyber-physical-social systems (CPSS) consist of battery-supplied devices with low
energy consumption requirements. It is essential to maintain the timing performance of …
energy consumption requirements. It is essential to maintain the timing performance of …
Energy-Efficient adaptive system reconfiguration for dynamic deadlines in autonomous driving
The increasing computing demands of autonomous driving applications make energy
optimizations critical for reducing battery capacity and vehicle weight. Current energy …
optimizations critical for reducing battery capacity and vehicle weight. Current energy …
Co-Located Parallel Scheduling of Threads to Optimize Cache Sharing
For hard-real time systems, cache memory increases execution time variability, increasing
the complexity of timing analysis. As such, cache memory is often treated exclusively as a …
the complexity of timing analysis. As such, cache memory is often treated exclusively as a …
A multi-level DPM approach for real-time DAG tasks in heterogeneous processors
F Reghenzani, A Bhuiyan… - 2021 IEEE Real-Time …, 2021 - ieeexplore.ieee.org
The modeling and analysis of real-time applications focus on the worst-case scenario
because of their strict timing requirements. However, many real-time embedded systems …
because of their strict timing requirements. However, many real-time embedded systems …
Segment based power-efficient scheduling for real-time DAG tasks on edge devices
Abstract Smart Mobile Devices (SMDs) are crucial for the edge computing paradigm's real-
world sensing. Real-time applications, which are computationally intensive and periodic with …
world sensing. Real-time applications, which are computationally intensive and periodic with …
Energy-harvesting-aware federated scheduling of parallel real-time tasks
This paper presents HEARTS, a multicore energy scheduling approach utilizing a federated
strategy designed for parallel real-time tasks of significant computational demands in …
strategy designed for parallel real-time tasks of significant computational demands in …