CRII: CNS: Supporting Mixed-Criticality Real-Time Systems on Heterogeneous Platforms

Texas State University - San Marcos, San Marcos TX

Investigators

Abstract

With the thriving applications in modern computing systems, there is a trend toward designing and implementing such systems in a consolidated manner for both scalability and sustainability. This trend leads to: first, applications, or tasks, of different criticalities that are supported on a common shared hardware platform; second, such platforms consist of computing processors that have different functionalities and capabilities, or heterogeneous processors. These may significantly impact the temporal predictability of the system, which is crucial for real-time systems where temporal guarantees must be validated prior to runtime. This project will conduct exploratory research on the real-time scheduling of mixed-criticality (MC) tasks on heterogeneous processors. The real-time scheduling analysis will provide provable guarantees on the temporal behaviors of the system. This research will investigate holistic methods and techniques that address the consolidation in both aspects of tasks and processors. This work will result in new system models that represent the MC tasks and the heterogeneous processors in an integrated manner. Based on the models, new scheduling algorithms will be developed to efficiently allocate the computing resources while the required temporal guarantees for the MC tasks are satisfied. System prototypes will be implemented to demonstrate and evaluate the effectiveness of the models and algorithms. These new models, algorithms, and prototypes will advance the understanding of both MC and heterogeneous scheduling in real-time systems, and will enable consolidated real-time system designs. This further benefits the efficiency, scalability, and affordability of a wide range of applications in internet of things (IoT) and cyber-¬physical systems (CPS) where temporal constraints commonly exist. As being conducted in a large Hispanic Serving Institution (HSI), this project will promote science, technology, engineering, and math (STEM) education and research for students from underrepresented groups and broaden their participation in computing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.