Real-time WSNs
Team
Faculty: Chenyang Lu, Yixin Chen
PhD Student: Abusayeed Saifullah, Chengjie Wu
Alumni: Octav Chipara, You Xu
Wireless Sensor-Actuator Networks (WSANs) represent a new generation of communication technology for industrial process control. A feedback control system in process industries (e.g., oil refineries) is implemented in a WSAN for process monitoring and control applications. With the adoption of WirelessHART, an open wireless sensor-actuator network standard, recent years have seen successful real-world deployment of WSANs for process monitoring and control. As today's process industries are gravitating towards wireless control systems, real-time scheduling issues are becoming increasingly important for WSANs.
Networked control loops impose stringent reliability and real-time requirements for communication between sensors and actuators. To support a feedback control loop, the network periodically delivers data from sensors to a controller and then delivers its control input data to the actuators within an end-to-end deadline. The direct effects of deadline misses in data communication may range from production inefficiency, equipment destruction to irreparable financial and environmental impacts.
Failures in wireless transmissions are prevalent in industrial environments due to channel noise, power failure, physical obstacle, multipath fading, and interference from coexisting wireless systems. Industrial standards such as WirelessHART deal with transmission failures through retransmissions, multi-path graph routing, and channel diversity. These features introduce unique challenges for real-time scheduling in industrial WSANs.
In a wireless control system, the control performance not only depends on the design of control algorithms, but also relies on real-time communication over the shared wireless network. The choice of sampling rates of the feedback control loops must balance between control performance and real-time communication. A low sampling rate usually degrades the control performance while a high sampling rate may cause excessive communication delays causing degraded performance. The coupling between real- time communication and control requires a scheduling-control co-design approach to optimize the control performance subject to stringent bandwidth constraints of the wireless network.
This research focuses on real-time scheduling issues for wireless sensor networks deployed for monitoring and control in process industries. Our goal is to develop novel scheduling policies, schedulability analysis, optimization, and system development for real-time wireless sensor networks.
Publications
- A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu, Y. Chen; Near Optimal Rate Selection for Wireless Control Systems; The 18th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '12), April 2012. PDF
- A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Priority Assignment for Real-time Flows in WirelessHART Networks; The 23rd Euromicro Conference on Real-Time Systems (ECRTS '11), July 2011, pp. 35--44. PDF
- A. Saifullah, Y. Xu, C. Lu, and Y. Chen; End-to-End Delay Analysis for Fixed Priority Scheduling in WirelessHART Networks; The 17th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '11), April 2011, pp. 13--22. PDF
- A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Real-time Scheduling for WirelessHART Networks; The 31st IEEE Real-Time Systems Symposium (RTSS '10), November 2010, pp. 150--159. PDF
- O. Chipara, C. Wu, C. Lu and W.G. Griswold, Interference-Aware Real-Time Flow Scheduling for Wireless Sensor Networks, Euromicro Conference on Real-Time Systems (ECRTS '11), July 2011. PDF
- O. Chipara, C. Lu and G.-C. Roman, Real-time Query Scheduling for Wireless Sensor Networks, IEEE Real-Time Systems Symposium (RTSS '07), December 2007. PDF
If you have any questions or comments, feel free to email Abusayeed Saifullah.
