Extending FreeRTOS to support dynamic and distributed mapping in multiprocessor systems

With the ever-increasing complexity of both embedded application workloads and multiprocessor platforms grows the demand for efficient mapping heuristics able of allocating several application workloads at runtime. The majority of promoted mapping techniques are bespoke implementations that consider an in-house operating system, which is developed to a particular architecture, restricting its adoption in other platforms. This work proposes a FreeRTOS extension that supports distributed task mapping heuristics, which enables to balance application workloads in multiprocessor architectures at runtime. Promoted extension is validated through a trustworthy number of scenarios considering large scale Cortex-M-based multiprocessor systems executing up to 600 application tasks.