Flexibility-Aware Network Resource Partitioning for Multi-State Real-Time Mission-Critical Applications

Tianyu Zhang; Kefan Wu; Jiachen Wang; Chuanyu Xue; Xiaobo Sharon Hu; Song Han

doi:10.1109/RTSS66672.2025.00032

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Conference proceeding

Flexibility-Aware Network Resource Partitioning for Multi-State Real-Time Mission-Critical Applications

Tianyu Zhang, Kefan Wu, Jiachen Wang, Chuanyu Xue, Xiaobo Sharon Hu and Song Han

Proceedings - Real-Time Systems Symposium, pp.297-310

12/02/2025

DOI: 10.1109/RTSS66672.2025.00032

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Abstract

A growing trend in large-scale industrial system design is the integration of multiple real-time, mission-critical applications over shared network infrastructures to reduce hardware costs and improve scalability. Recent advances in network resource partitioning techniques provide practical mechanisms for managing these applications hierarchically while maintaining operational isolation. However, as system complexity increases, applications often exhibit multi-state behaviors that challenge the system's ability to meet stringent timing requirements - especially under static resource partitions. While dynamic resource reconfiguration can restore feasibility, it is typically costly and disruptive in industrial environments. To address this challenge, we propose a flexibility-aware network resource partitioning framework that introduces a novel metric - partition flexibility - to quantify how effectively a resource partition supports an application's state transitions. Using this metric, we develop efficient strategies for both static partition allocation and dynamic partition adjustment, with the goal of minimizing reconfiguration overhead. We validate our framework design through a real-world case study involving a NASA extra-terrestrial habitat system deployed on a time-sensitive networking (TSN) testbed. Extensive simulations further demonstrate that the proposed partitioning framework reduces \mathbf{5 6. 4 \%} reconfigurations compared to the state-of-the-art methods.

Dynamic scheduling

Hardware

Measurement

Mission critical systems

NASA

Real-time systems

Resource management

Scalability

Timing

Details

Title: Subtitle: Flexibility-Aware Network Resource Partitioning for Multi-State Real-Time Mission-Critical Applications
Creators: Tianyu Zhang - University of Iowa
Kefan Wu - University of Connecticut
Jiachen Wang - University of Connecticut
Chuanyu Xue - University of Connecticut
Xiaobo Sharon Hu - University of Notre Dame
Song Han - University of Connecticut
Resource Type: Conference proceeding
Publication Details: Proceedings - Real-Time Systems Symposium, pp.297-310
DOI: 10.1109/RTSS66672.2025.00032
eISSN: 2576-3172
Publisher: IEEE
Grant note: 2008463 / NSF (10.13039/100000001)
Language: English
Date published: 12/02/2025
Academic Unit: Computer Science
Record Identifier: 9985116065202771

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