arXiv subjects

Ruide Cao

Publications and source records attributed to Ruide Cao.

3 recordsLinked to original sources

arXiv2026

ARTSN: Exact and Adaptive Self-triggered Traffic Scheduling for ARTS Networks

Autonomous real-time systems (ARTS), such as self-driving vehicles and robotic assembly lines, are increasingly deployed to improve efficiency, accuracy, and responsiveness with reduced human intervention. In ARTS networks, self-triggered (ST) traffic-initiated by internal decision-making rather than fixed schedules or external events-is becoming prevalent and plays a critical role in enabling timely autonomous actions. However, existing network schedulers do not adequately support ST traffic due to two inherent challenges: volatility, where bounded processing jitter leads to uncertain arrival times, and absence, where reserved network resources remain underutilized when ST traffic does not materialize. To address these challenges, we propose ARTSN, an ST-tailored scheduling paradigm built upon time-sensitive networking (TSN). ARTSN introduces two key techniques: (1) an exact offline scheduling method that leverages the inferable arrival information of ST traffic for precise time-slot reservation, and (2) an adaptive online slot-release mechanism that dynamically reclaims unused reservations when ST traffic is absent. Extensive experiments on both a TSN simulator and a real-world testbed show that ARTSN significantly improves schedulability, scalability, and efficiency over state-of-the-art methods while maintaining reliable transmission guarantees.

cs.NI↗

arXiv2025

SAGkit: A Python SAG Toolkit for Response Time Analysis of Hybrid-Triggered Jobs

For distributed control systems, modern latency-critical applications are increasingly demanding real-time guarantees and robustness. Response-time analysis (RTA) is useful for this purpose, as it helps analyze and guarantee timing bounds. However, conventional RTA methods struggle with the state-space explosion problem, especially in non-preemptive systems with release jitter and execution time variations. In this paper, we introduce SAGkit, a Python toolkit that implements the schedule-abstraction graph (SAG) framework. SAGkit novelly enables exact and sustainable RTA of hybrid-triggered jobs by allowing job absence on the SAG basis. Our experiments demonstrate that SAGkit achieves exactness with acceptable runtime and memory overhead. This lightweight toolkit empowers researchers to analyze complex distributed control systems and is open-access for further development.

cs.DC↗

arXiv2025

A User-to-User Resource Reselling Game in Open RAN with Buffer Rollover

The development of the Open RAN (O-RAN) framework helps enable network slicing through its virtualization, interoperability, and flexibility. To improve spectral efficiency and better meet users' dynamic and heterogeneous service demands, O-RAN's flexibility further presents an opportunity for resource reselling of unused physical resource blocks (PRBs) across users. In this work, we propose a novel game-based user-to-user PRB reselling model in the O-RAN setting, which models the carryover of unmet demand across time slots, along with how users' internal buffer states relate to any PRBs purchased. We formulate the interplay between the users as a strategic game, with each participant aiming to maximize their own payoffs, and we prove the existence and uniqueness of the Nash equilibrium (NE) in the game. We furthermore propose an iterative bidding mechanism that converges to this NE. Extensive simulations show that our best approach reduces data loss by 30.5% and spectrum resource wastage by 50.7% while significantly improving social welfare, compared to its absence.

cs.NI↗