Mobile devices have been increasingly deployed in large-scale cyber-physical systems (CPS) to traverse the field and retrieve data measurements from designated physical entities with stringent performance requirements. This work studies the availability-constrained real-time data retrieval problem in CPS with a speed adjustable mobile device (AFDR-SA). The goal is to maintain the temporal validity of the real-time data to be retrieved in the system while meeting the data availability constraints imposed by the communication range between the mobile device and the physical entities. A dynamic programming (DP)-based optimal algorithm is proposed for a special but commonly presented scenario where the retrieval times of individual data items are of the same length. Based on this optimal algorithm, an effective heuristic method is further developed for the general case where data items can have arbitrary retrieval times. The effectiveness of the proposed methods are validated through extensive experiments. Our results demonstrate the optimality of the DP-based algorithm, and show that the heuristic method outperforms the state-of-the-art schemes and performs close to the optimal solution obtained by the exhaustive search with much less computational overhead.

Keep Fresh: Real-time Data Retrieval with Speed Adaptation in Mobile Cyber-Physical Systems

Real-time end-to-end task scheduling in networked control systems (NCSs) requires the joint consideration of both network and computing resources to guarantee the desired quality of service (QoS). This paper introduces a new model for composite resource scheduling (CRS) in real-time networked control systems, which considers a strict execution order of sensing, computing, and actuating segments based on the control loop of the target NCS. We prove that the general CRS problem is NP-hard and study two special cases of the CRS problem. The first case restricts the computing and actuating segments to have unit-size execution time while the second case assumes that both sensing and actuating segments have unit-size execution time. We propose an optimal algorithm to solve the first case by checking the intervals with 100% network resource utilization and modify the deadlines of the tasks within those intervals to prune the search. For the second case, we propose another optimal algorithm based on a novel backtracking strategy to check the time intervals with the network resource utilization larger than 100% and modify the timing parameters of tasks based on these intervals. For the general case, we design a greedy strategy to modify the timing parameters of both network segments and computing segments within the time intervals that have network and computing resource utilization larger than 100%, respectively. The correctness and effectiveness of the proposed algorithms are verified through extensive experiments.

Composite Resource Scheduling for Networked Control Systems

**Session chair:** Martina Maggio

- 25 min: [**(Outstanding Paper) Concurrent Order Dispatch for Instant Delivery with Time-Constrained Actor-Critic Reinforcement Learning**](https://conferences.computer.org/rtsspub/pdfs/RTSS2021-23beZleJJDdiozCiQ9rzXD/280200a176/280200a176.pdf), *Baoshen Guo, Shuai Wang, Yi Ding, Guang Wang, Suining He, Desheng Zhang and Tian He*
- 25 min: [**Keep Fresh: Real-time Data Retrieval with Speed Adaptation in Mobile Cyber-Physical Systems**](https://conferences.computer.org/rtsspub/pdfs/RTSS2021-23beZleJJDdiozCiQ9rzXD/280200a304/280200a304.pdf), *Chenchen Fu, Xiaoxing Qiu, Zelin Yun, Song Han, Weiwei Wu and Jason Xue*
- 25 min: [**Catch Me If You Learn: Real-Time Attack Detection and Mitigation in Learning Enabled CPS**](https://conferences.computer.org/rtsspub/pdfs/RTSS2021-23beZleJJDdiozCiQ9rzXD/280200a136/280200a136.pdf), *Ipsita Koley, Sunandan Adhikary and Soumyajit Dey*
- 25 min: [**Composite Resource Scheduling for Networked Control Systems**](https://conferences.computer.org/rtsspub/pdfs/RTSS2021-23beZleJJDdiozCiQ9rzXD/280200a162/280200a162.pdf), *Peng Wu, Chenchen Fu, Tianyu Wang, Minming Li, Yingchao Zhao, Jason Xue and Song Han*



4.12 - Cyber-Physical Systems

technical paper

 **RTSS 2021** has successfully concluded. Hope you have enjoyed it, and look forward to seeing you next year in person.
    Announcement for the Awards:
 * Best Paper Award goes to: Monte Carlo Response-Time Analysis, Sergey Bozhko, Georg von der Brüggen, and Björn Brandenburg
 * Best Student Paper Award goes to: Automatic Energy-Hotspot Detection and Elimination in Real-Time Deeply Embedded Systems, Mohsen Shekarisaz, Lothar Thiele, and Mehdi Kargahi.
 * Best Solution Award for Industry Session goes to: Toward Real-Time Guaranteed Scheduling for Autonomous Driving Systems. Jinghao Sun, Tianyi Wang, Kailu Duan, Bin Lu, Jiankang Ren, Zhishan Guo, and Guozhen Tan.



IEEE RTSS 2021

The IEEE Real-Time Systems Symposium (RTSS) is the premier conference in the field of real-time systems, and is a venue for researchers and practitioners to showcase innovations covering all aspects of real-time systems, including theory, design, analysis, implementation, evaluation, and experience. 

Chenchen Fu

2

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Keep Fresh: Real-time Data Retrieval with Speed Adaptation in Mobile Cyber-Physical Systems

Composite Resource Scheduling for Networked Control Systems

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