TY - GEN
T1 - Real-Time Scheduling for Event-Triggered and Time-Triggered Flows in Industrial Wireless Sensor-Actuator Networks
AU - Jin, Xi
AU - Saifullah, Abusayeed
AU - Lu, Chenyang
AU - Zeng, Peng
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Wireless sensor-actuator networks enable an efficient and cost-effective approach for industrial sensing and control applications. To satisfy the real-time requirement of such applications, these networks adopt centralized scheduling algorithms to optimize the real-time performance based on global information. Existing centralized algorithms mostly focus on scheduling time-triggered flows. They cannot effectively schedule event-triggered flows due to the dynamics and unpredictability of events. In this paper, we propose three fundamental centralized algorithms that reserve as few resources as possible for event-triggered flows such that the real-time performance of time-triggered flows is not affected. We then analyze their advantages and disadvantages. Based on the analysis, we combine their advantages, including those in terms of their resource requirements, into a centralized algorithm. Finally, we conduct extensive simulations based on both real topologies and random topologies. The simulations indicate that for most test cases the schedulability of our combined algorithm is close to optimal solutions.
AB - Wireless sensor-actuator networks enable an efficient and cost-effective approach for industrial sensing and control applications. To satisfy the real-time requirement of such applications, these networks adopt centralized scheduling algorithms to optimize the real-time performance based on global information. Existing centralized algorithms mostly focus on scheduling time-triggered flows. They cannot effectively schedule event-triggered flows due to the dynamics and unpredictability of events. In this paper, we propose three fundamental centralized algorithms that reserve as few resources as possible for event-triggered flows such that the real-time performance of time-triggered flows is not affected. We then analyze their advantages and disadvantages. Based on the analysis, we combine their advantages, including those in terms of their resource requirements, into a centralized algorithm. Finally, we conduct extensive simulations based on both real topologies and random topologies. The simulations indicate that for most test cases the schedulability of our combined algorithm is close to optimal solutions.
UR - https://www.scopus.com/pages/publications/85068222270
U2 - 10.1109/INFOCOM.2019.8737373
DO - 10.1109/INFOCOM.2019.8737373
M3 - Conference contribution
AN - SCOPUS:85068222270
T3 - Proceedings - IEEE INFOCOM
SP - 1684
EP - 1692
BT - INFOCOM 2019 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Conference on Computer Communications, INFOCOM 2019
Y2 - 29 April 2019 through 2 May 2019
ER -