Independent Task Scheduling in Multi‐Core Systems: A Hardware‐Based Approach for Optimising Energy and Thermal Efficiency

Task scheduling in real‐time multi‐core systems is crucial for meeting stringent timing requirements, especially as embedded systems become increasingly prevalent. Battery‐powered systems, in particular, require energy‐efficient schedulers to regulate processor speed and temperature. Current software‐based schedulers face limitations, such as overhead, latency and inefficiencies, making it challenging to balance performance with energy and thermal management. This highlights the need for more dynamic schedulers in heterogeneous multi‐core processor environments, particularly for independent task scheduling, which must address these challenges while optimising both energy consumption and temperature control. This paper presents an online distributed hardware scheduler designed specifically for independent tasks, utilising the earliest deadline first (EDF) algorithm to manage hard real‐time tasks on multi‐core embedded systems. Implementing this scheduler in hardware reduces clock cycles, improves efficiency and lowers latency compared to software‐based solutions. It dynamically adapts to real‐time tasks without compromising predictability or introducing significant overhead. The scheduler optimises energy consumption and temperature management, addressing both dynamic and static energy demands. Results show a reduction of in dynamic energy, in static energy and in temperature compared to the high‐performance real‐time hardware scheduler (HRHS), while maintaining overall system performance and efficiency.