In embedded system, a real-time operating system (RTOs) is often used to structure the application code and ensure that the deadlines are met by reacting on events in the environment by executing the functions within precise time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical metrics. Generally RTOs are implemented in software, which in turns increases computational overheads, jitter and memory footprint which can be reduced even if not remove completely by utilizing latest FPGA technology, which enables the implementation of a full featured and flexible hardware based RTOs. Scheduling algorithms play an important role in the design of real-time systems. This paper proposes the novel FIS based adaptive hardware task scheduler for multiprocessor systems that minimizes the processor time for scheduling activity which uses fuzzy logic to model the uncertainty at first stage along with adaptive framework that uses feedback which allows processors share of task running on multiprocessor to be controlled dynamically at runtime. This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of total task and thus improves efficiency of the entire real-time system. The increased computation overheads resulted from proposed model can be compensated by exploiting the parallelism of the hardware as being migrated to FPGA.
Harkut and Ali REF used RTOS and FPGA technology in order to develop a novel fuzzy logic based adaptive hardware scheduler for multiprocessor systems that minimizes the processor time for scheduling activity.
Adaptive Fuzzy Hardware Scheduler for Real Time Operating System
International Journal of Computing
Computer Science