Open AccessPerformance optimization of task intensive real‐time applications on multicore ECUs—A hybrid scheduler
Author(s) -
Mishra Geetishree,
Hegde Rajeshwari
Publication year - 2021
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/tje2.12059
Subject(s) - multi core processor , computer science , embedded system , autosar , scheduling (production processes) , human multitasking , context switch , software , distributed computing , operating system , engineering , psychology , operations management , cognitive psychology
In the current approach of automotive electronic system design, the multicore processors have prevailed to achieve high computing performance at low thermal dissipation. Multicore processors offer functional parallelism that helps in meeting the safety critical requirements of vehicles. The number of Electronic Control Units (ECUs) in high‐end cars could be reduced by conglomerating more functions into a multicore ECU. AUTOSAR stack has been designed to support the applications developed for multicore ECUs. The real challenges lie in adapting new design methods while developing sophisticated applications with multicore constraints. It is imperative to utilize the most of multicore computational capability towards enhancing the overall performance of ECUs. In this context, the scheduling of the real‐time multitasking software components by the operating system is one of the challenging issues to be addressed. Here, the state‐of‐the‐art scheduling algorithm is reviewed and its merits and limitations are identified. A hybrid scheduler has been proposed, tested and compared with the state‐of‐the‐art algorithm that offers better performance in terms of CPU utilization, average response time and deadline missing rate both in normal and high load conditions.