TY - GEN
T1 - Enabling wireless network support for gain scheduled control
AU - Gallenmüller, Sebastian
AU - Glebke, René
AU - Günther, Stephan
AU - Hauser, Eric
AU - Leclaire, Maurice
AU - Reif, Stefan
AU - Rüth, Jan
AU - Schmidt, Andreas
AU - Carle, Georg
AU - Herfet, Thorsten
AU - Schröder-Preikschat, Wolfgang
AU - Wehrle, Klaus
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/3/25
Y1 - 2019/3/25
N2 - To enable cooperation of cyber-physical systems in latency-critical scenarios, control algorithms are placed in edge systems communicating with sensors and actuators via wireless channels. The shift from wired towards wireless communication is accompanied by an inherent lack of predictability due to interference and mobility. The state of the art in distributed controller design is proactive in nature, modeling and predicting (and potentially oversimplifying) channel properties stochastically or pessimistically, i. e., worst-case considerations. In contrast, we present a system based on a real-time transport protocol that is aware of application-level constraints and applies run-time measurements for channel properties. Our run-time system utilizes this information to select appropriate controller instances, i. e., gain scheduling, that can handle the current conditions. We evaluate our system empirically in a wireless testbed employing a shielded environment to ensure reproducible channel conditions. A series of measurements demonstrates predictability of latency and potential limits for wireless networked control.
AB - To enable cooperation of cyber-physical systems in latency-critical scenarios, control algorithms are placed in edge systems communicating with sensors and actuators via wireless channels. The shift from wired towards wireless communication is accompanied by an inherent lack of predictability due to interference and mobility. The state of the art in distributed controller design is proactive in nature, modeling and predicting (and potentially oversimplifying) channel properties stochastically or pessimistically, i. e., worst-case considerations. In contrast, we present a system based on a real-time transport protocol that is aware of application-level constraints and applies run-time measurements for channel properties. Our run-time system utilizes this information to select appropriate controller instances, i. e., gain scheduling, that can handle the current conditions. We evaluate our system empirically in a wireless testbed employing a shielded environment to ensure reproducible channel conditions. A series of measurements demonstrates predictability of latency and potential limits for wireless networked control.
KW - Control
KW - Edge computing
KW - Gain scheduling
KW - Latency-awareness
KW - Networking
KW - Reproducible wireless measurements
UR - http://www.scopus.com/inward/record.url?scp=85063918408&partnerID=8YFLogxK
U2 - 10.1145/3301418.3313943
DO - 10.1145/3301418.3313943
M3 - Conference contribution
AN - SCOPUS:85063918408
T3 - EdgeSys 2019 - Proceedings of the 2nd ACM International Workshop on Edge Systems, Analytics and Networking, Part of EuroSys 2019
SP - 36
EP - 41
BT - EdgeSys 2019 - Proceedings of the 2nd ACM International Workshop on Edge Systems, Analytics and Networking, Part of EuroSys 2019
PB - Association for Computing Machinery, Inc
T2 - 2nd ACM International Workshop on Edge Systems, Analytics and Networking, EdgeSys 2019, Part of EuroSys 2019
Y2 - 25 March 2019 through 25 March 2019
ER -