Scheduling real-time multi-processor systems with distance-constrained tasks using the early-release-fair model

A hard real-time system is one whose correctness depends not only on the logical result, but also when the results are produced. While many techniques have been proposed for single processor real-time systems, multiprocessor systems have not been studied so extensively. In this paper, we mainly propose two variant (DCTS) by using the Early-Release-Fair (ERfair) and Proportionate-fair,(Pfair) model with integral assumptions for identical multi-processor real-time systems. ERfair is a scheduling model for real-time tasks on a multiprocessor system. On the different definitions of distance constraint, we propose two efficient scheduling algorithms designed to probe whether the distance constraints of all ER-fair tasks can be guaranteed. If the distance constraints cannot be guaranteed, then the proposed algorithms gather the unfeasible tasks and inflate them with a reweighting function. The proposed algorithms are linear-time and most suitable for dynamic systems. The experimental results reveal that the proposed algorithms increase significantly the ratio of schedulable task sets.