Overload provisioning in mixed-criticality cyber-physical systems

Abstract

Cyber-physical systems are an emerging class of applications that require tightly coupled interaction between the computational and physical worlds. These systems are typically realized using sensor/actuator interfaces connected with processing backbones. Safety is a primary concern in cyber-physical systems since the actuators directly influence the physical world. However, unexpected or unusual conditions in the physical world can manifest themselves as increased workload demands being offered to the computational infrastructure of a cyber-physical system. Guaranteeing system safety under overload conditions is therefore a prime concern in developing and deploying cyber-physical systems. In this work, we study this problem in the context of a radar surveillance system, where tasks have different levels of criticality or influence on system safety . In the face of overloads, we observe that the desirable property in such systems is that the more critical tasks continue to meet their timing requirements. We capture this mixed-criticality overload requirement using a formal overload-tolerance metric called ductility . Using this overload-tolerance metric, we first develop our solution in the context of uniprocessor systems, where we show that Zero-Slack scheduling (ZS) algorithms can be used to improve the overload behavior in mixed-criticality cyber-physical systems compared to existing fixed-priority scheduling algorithms like Rate-Monotonic Scheduling (RMS) and Criticality-As-Priority-Assignment (CAPA). Leveraging these results, we then develop a criticality-aware task allocation algorithm called Compress-on-Overload Packing (COP) for dealing with multiprocessor cyber-physical systems. Evaluation results show that COP achieves up to five times better ductility than traditional load balancing bin-packing algorithms like Worst-Fit Decreasing (WFD). Finally, we apply ZS and COP to the radar surveillance system to demonstrate the resulting improvement in system overload behavior. Our implementation of the Zero-Slack scheduler is available as a part of the Linux/RK project, which provides resource kernel extensions for Linux.