AUTOSAR Extensions for Predictable Task Synchronization in MultiCore ECUs

Multi-core processors are becoming increasingly prevalent, with multiple multi-core solutions being offered for the automotive sector. Recognizing this trend, the AUTomotive Open System ARchitecture (AUTOSAR) standard version 4.0 has introduced support for multi-core embedded real-time operating systems. A key element of the AUTOSAR multi-core specification is the spinlock mechanism for inter-core task synchronization. In this paper, we study this spinlock mechanism from the standpoint of timing predictability. We describe the timing uncertainties introduced by standard test-and-set spinlock mechanisms, and provide a predictable priority-driven solution for inter-core task synchronization. The proposed solution is to arbitrate critical sections using the well-established Multi-processor Priority Ceiling Protocol [3], which is the multiprocessor version of the ceiling protocol for uniprocessors [1, 2] used by AUTOSAR. We also present the associated analysis that can be used in conjunction with the AUTOSAR task model to bound the worst-case waiting times for accessing shared resources. The timing predictability provided by our protocol is an important requirement for automotive applications from both certification and validation standpoints.</p

Resource Allocation in Distributed Mixed-Criticality Cyber-Physical Systems

Large-scale distributed cyber-physical systems will have many sensors/actuators (each with local micro-controllers), and a distributed communication/computing backbone with multiple processors. Many cyber-physical applications will be safety critical and in many cases unexpected workload spikes are likely to occur due to unpredictable changes in the physical environment. In the face of such overload scenarios, the desirable property in such systems is that the most critical applications continue to meet their deadlines. In this paper, we capture this mixed-criticality property by developing a formal overload-resilience metric called ductility. The generality of ductility enables it to evaluate any scheduling algorithm from the perspective of mixed-criticality cyber-physical systems. In distributed cyber-physical systems, this ductility is the result of both the task-to-processor packing (a.k.a bin packing) and the uniprocessor scheduling algorithms used. In this paper, we present a ductility-maximization packing algorithm to complement our previous work on mixed-criticality uniprocessor scheduling [6]. Our packing algorithm, known as Compress-on-Overload Packing (COP) is a criticality-aware greedy bin-packing algorithm that maximizes the tolerance of high-criticality tasks to overloads. We compare the ductility of COP against the Worst-Fit Decreasing (WFD) bin-packing heuristic used traditionally for load balancing in distributed systems, and show that the performance of COP dominates WFD in the average case and can reach close to five times better ductility when resources are limited. Finally, we illustrate the practical use of COP in distributed cyber-physical systems using a radar surveillance application, and provide an overview of the entire process from assigning task criticality levels to evaluating its performance

Results of SEI Independent Research and Development Projects

The Software Engineering Institute (SEI) annually undertakes several independent research and development (IRAD) projects. These projects serve to (1) support feasibility studies investigating whether further work by the SEI would be of potential benefit and (2) support further exploratory work to determine whether there is sufficient value in eventually funding the feasibility study work as an SEI initiative. Projects are chosen based on their potential to mature and/or transition software engineering practices, develop information that will help in deciding whether further work is worth funding, and set new directions for SEI work. This report describes the IRAD projects that were conducted during fiscal year 2009 (October 2008 through September 2009)

Results of SEI Independent Research and Development Projects (FY 2010)

The Software Engineering Institute (SEI) annually undertakes several independent research and development (IRAD) projects. These projects serve to (1) support feasibility studies investigating whether further work by the SEI would be of potential benefit and (2) support further exploratory work to determine whether there is sufficient value in eventually funding the feasibility study work as an SEI initiative. Projects are chosen based on their potential to mature and/or transition software engineering practices, develop information that will help in deciding whether further work is worth funding, and set new directions for SEI work. This report describes the IRAD projects that were conducted during fiscal year 2010 (October 2009 through September 2010).</p