Real-Time Systems

Papers
(The TQCC of Real-Time Systems is 3. 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 2021-10-01 to 2025-10-01.)
ArticleCitations
Shielded reinforcement learning for fault-tolerant scheduling in real-time systems35
Connecting the physical space and cyber space of autonomous systems more closely14
Generalized self-cueing real-time attention scheduling with intermittent inspection and image resizing12
Characterizing global work-conserving scheduling tardiness with uniform instances on multiprocessors11
Editorial on the special issue of RTNS 202011
Multi-core interference over-estimation reduction by static scheduling of multi-phase tasks9
Worst case response time analysis for completely fair scheduling in Linux systems8
To MILP or not to MILP? On AI techniques for the design and optimization of real-time systems8
Extending a predictable machine learning framework with efficient gemm-based convolution routines7
Exploring AMD GPU scheduling details by experimenting with “worst practices”5
Cutting-plane algorithms for preemptive uniprocessor scheduling problems5
Design optimization for real-time systems with sustainable schedulability analysis5
Optimally ordering IDK classifiers subject to deadlines5
A framework for multi-core schedulability analysis accounting for resource stress and sensitivity5
Resource Management for Stochastic Parallel Synchronous Tasks: Bandits to the Rescue5
Feasibility analysis for HPC-DAG tasks5
Statistical verification of autonomous system controllers under timing uncertainties4
From cache and memory management to WCET analysis3
Supporting AI-powered real-time cyber-physical systems on heterogeneous platforms via hypervisor technology3
Position paper: deep reinforcement learning for real-time resource management3
A formal framework to design and prove trustworthy memory controllers3
An MDP-based solution for the energy minimization of non-clairvoyant hard real-time systems3
The advantage of the GPU as a real-time AI accelerator3
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