Speeding Up the Schedulability Analysis and Priority Assignment of Sporadic Tasks Under Uniprocessor FPNS

Abstract

Fixed-priority non-preemptive scheduling (FPNS) is widely used in practice because of its simplicity and predictability. This article aims to enhance the efficiency of the schedulability analysis and priority assignment of sporadic tasks under uniprocessor FPNS. To speed-up the schedulability analysis, we first improve the state-of-the-art worst-case response time analysis for uniprocessor fixed-priority non-preemptive scheduling. In addition, we present two special conditions under which the worst-case response time of a task can be analyzed from its first job, which further improves the efficiency of the analysis. To accelerate the priority assignment, we present two priority-assignment algorithms based on the improved Audsley's algorithm: improved Audsley-based longest deadline first (IA-LDF) and improved Audsley-based longest worst-case execution time first (IA-LCF). The numerical experiments show that IA-LDF and IA-LCF can lead to 31.2% and 36% decrease in runtime compared to longest deadline first (LDF) and longest worst-case execution time first (LCF), respectively.