The invention discloses a real-time multiprocessor scheduling method based on boundary proportional fair optimization, aims to solve the problems of high context switching overhead and implementation complexity of a PFair
algorithm in a multiprocessor environment, and aims to optimize a core mechanism of a PD2
algorithm, including reconstruction of a priority tuple and introduction of an intelligent
early release rule. The
idle time of the processor is obviously reduced by 19%; meanwhile, the
system is integrated into a SchedCAT framework, a red-black tree is used for managing a subtask
queue to achieve efficient scheduling, a
quantum scheduler controls time
jitter within 5 microseconds, and the migration cost is reduced in combination with a cache sensing strategy; through comprehensive
verification of x86 and ARM platforms, under the harsh condition that the
utilization rate of a processor reaches 100%, the context switching overhead is reduced by 18-22%, 32-256 task high-load scenes are supported, the real-time performance is ensured to be stable, the method is suitable for the high-requirement fields such as an automatic driving control module and an industrial real-
time system, and finally industrial application landing is promoted through
open source implementation (SchedCAT v2.3).