Biblio

Filters: Author is Q. Wang  [Clear All Filters]
2018-05-25
F. Miao, S. Han, S. Lin, J. Stankovic, Q. Wang, D. Zhang, T. He, G. J. Pappas.  2016.  Data-Driven Robust Taxi Dispatch Approaches. 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS). :1-1.
2017-02-21
Q. Wang, Y. Ren, M. Scaperoth, G. Parmer.  2015.  "SPeCK: a kernel for scalable predictability". 21st IEEE Real-Time and Embedded Technology and Applications Symposium. :121-132.

Multi- and many-core systems are increasingly prevalent in embedded systems. Additionally, isolation requirements between different partitions and criticalities are gaining in importance. This difficult combination is not well addressed by current software systems. Parallel systems require consistency guarantees on shared data-structures often provided by locks that use predictable resource sharing protocols. However, as the number of cores increase, even a single shared cache-line (e.g. for the lock) can cause significant interference. In this paper, we present a clean-slate design of the SPeCK kernel, the next generation of our COMPOSITE OS, that attempts to provide a strong version of scalable predictability - where predictability bounds made on a single core, remain constant with an increase in cores. Results show that, despite using a non-preemptive kernel, it has strong scalable predictability, low average-case overheads, and demonstrates better response-times than a state-of-the-art preemptive system.