Optimization-based approach to cross-layer resource management in Wireless networked control systems
Wireless Networked Control Systems (NCS) are increasingly deployed to monitor and control Cyber-Physical Systems (CPS), as wireless network provides great convenience in terms of fully mobile operation, rapid deployment and flexible installation. To support mission critical operations of CPS, NCS need to achieve and maintain a desirable level of performance. In the wireless network however, resources are constrained by limited bandwidth and power; dynamic user behaviors and resource interference also aggravate network uncertainties and introduce random packet loss and time-varying delay. These resource constraints and network dynamics pose significant challenges and require a fresh treatment to the design of wireless NCS. In this dissertation, we investigate the problem of resource management in wireless networks to support NCS with stringent Quality of Service (QoS) requirements. The capability of adaptive resource management is crucial for NCS to fully exploit the available resource and achieve optimal performance. The interaction between networking systems and control systems is the key to adaptive resource management. It allows informed operation decisions within individual systems to collaboratively achieve a global management objective. In particular, we present a cross-layer approach to support interactions between wireless networks and networked control systems. The cross-layer design aligns with network layered architecture, thus is feasible for broader adoption in real-world deployment. We consider two information exchange directions in our design. When the control systems deliver their performance requirements to the wireless network, the network adjusts its operation parameters to facilitate the performance optimization of the control systems; When the wireless network passes congestion signals to the control systems, the control systems dynamically adapt their sampling rates to preserve optimal performance. We further explore the cross-layer interactions between the two systems and among layers within the networking protocol stack, which combine the design of control system sampling rate adaptation and the network scheduling. To arbitrate the resource sharing among multiple control systems, we present a new fairness model for wireless network based on the game theoretical framework, and evaluate the impact of resource sharing regions approximated by different neighborhood models.