Cognitive Robotics (Jan 2021)
Research on semi-partitioned scheduling algorithm in mixed-criticality system
Abstract
In order to overcome the problem that in a mixed-critical system, once the critical level of the system changes, lower-critical tasks may be abandoned in order to ensure the schedulability of higher-critical tasks. A semi-partitioned scheduling algorithm SPBRC, which is based on a homogeneous multi-processor mixed-criticality platform and integrates the advantages and disadvantages of global scheduling and partitioned scheduling is proposed. First-fit and worst-fit bin-packing algorithms are firstly used in this method to sort high and low critical tasks separately, all high critical tasks as fixed task allocation in different processors in turns, and then distribute the lower-critical tasks. When the criticality of processor changes, lower-cirtical tasks will be allowed to migrate to the processor that is paired with the processor and is in low-critical mode, rather than abandoned. Thus, the overall performance of the system is improved. The simulation experiment verifies the effectiveness of this method in reducing the task loss rate and job loss rate.