Real-Time Systems

Papers
(The TQCC of Real-Time Systems is 2. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-09-01 to 2025-09-01.)
ArticleCitations
Connecting the physical space and cyber space of autonomous systems more closely34
Generalized self-cueing real-time attention scheduling with intermittent inspection and image resizing12
Shielded reinforcement learning for fault-tolerant scheduling in real-time systems12
Editorial on the special issue of RTNS 202011
Characterizing global work-conserving scheduling tardiness with uniform instances on multiprocessors10
Multi-core interference over-estimation reduction by static scheduling of multi-phase tasks9
Extending a predictable machine learning framework with efficient gemm-based convolution routines8
Worst case response time analysis for completely fair scheduling in Linux systems8
Design optimization for real-time systems with sustainable schedulability analysis5
Exploring AMD GPU scheduling details by experimenting with “worst practices”5
A framework for multi-core schedulability analysis accounting for resource stress and sensitivity5
To MILP or not to MILP? On AI techniques for the design and optimization of real-time systems5
Statistical verification of autonomous system controllers under timing uncertainties5
Resource Management for Stochastic Parallel Synchronous Tasks: Bandits to the Rescue5
Feasibility analysis for HPC-DAG tasks4
Cutting-plane algorithms for preemptive uniprocessor scheduling problems3
Position paper: deep reinforcement learning for real-time resource management3
A formal framework to design and prove trustworthy memory controllers3
Optimally ordering IDK classifiers subject to deadlines3
Buffer dimensioning per frames in packet networks2
Configuration optimization for heterogeneous time-sensitive networks2
The shape of a DAG: bounding the response time using long paths2
CertiCAN certifying CAN analyses and their results2
The advantage of the GPU as a real-time AI accelerator2
From cache and memory management to WCET analysis2
Inference serving with end-to-end latency SLOs over dynamic edge networks2
Supporting AI-powered real-time cyber-physical systems on heterogeneous platforms via hypervisor technology2
An MDP-based solution for the energy minimization of non-clairvoyant hard real-time systems2
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