High-Performance Real-Time Scheduling

Abstract

This chapter presents a multiple parallel applications scheduling optimization with respect to high performance and timing constraint. We first present the fairness and the whole priority scheduling algorithms from high performance and timing constraint perspectives, respectively. Thereafter, we mix these two algorithms to present the partial priority scheduling algorithm, which can satisfy the deadlines of more high-priority applications and reduce the overall schedule length of the system. The partial priority scheduling algorithm is implemented by preferentially scheduling the partial tasks of high-priority applications, and then fairly scheduling their remaining tasks with all the tasks of low-priority applications. Further, each application has different criticality levels (e.g., severity), and missing the deadlines of certain high-criticality functions may cause fatal injuries to people. Therefore, we present the multiple heterogeneous earliest finish time (F_MHEFT) algorithm for a multiple parallel applications with the mixed-criticality on heterogeneous distributed embedded systems. Next, we propose a novel algorithm called the deadline-span of multiple heterogeneous earliest finish time (D_MHEFT), which is a scheduling algorithm for multiple mixed-criticality applications. The F_MHEFT algorithm aims at improving the performance of systems, while the D_MHEFT algorithm tries to meet the deadlines of more high-criticality functions by sacrificing a certain performance. At the end of this chapter, different experiments will be presented and their results demonstrate that the partial priority scheduling algorithm achieves the significant optimization, and the D_MHEFT algorithm can significantly reduce the deadline miss ratio (DMR) while keeping satisfactory performance over existing methods.