Performance optimization of task intensive real time applications on multicore ECUs - a hybrid scheduler

Abstract

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 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 key issues to be addressed. In this paper, 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.

Towards more accurate iris recognition system by using hybrid approach for feature extraction along with classifier

“…While the source scaling and wavelet meanings are correspondingly formulated in (6) as monitors [35].…”

“…Remember that both the scrabbling and wavelet meanings can be prolonged in terms of basis mounting purposes of the next higher purpose which shows in (7) as [35], [36].…”