A Novel Task-to-Processor Assignment Approach for Optimal Multiprocessor Real-Time Scheduling

Recent decades have recognized the popularization of multiprocessor architectures in real-time embedded systems. Real-time task scheduling in such systems has become a challenging problem as a result. In this paper, we are presenting an optimal scheduling algorithm, which can successfully schedule any task sets with no deadline miss if the total utilization of tasks does not exceed the capacity of the involved system. The proposed algorithm called LLA introduces a so-called fixed task-scheduling plan for every time interval that is defined as the time period between two consecutive job releases. At the beginning of each interval, LAA makes the scheduling plan by predicting tasks' requested amount of execution time within the interval and then arranging these amounts to processors appropriately respecting to requirements of scheduling. By this approach, LAA can extremely reduce the number of scheduler invocations to the number of job releases. Furthermore, simulation results show that our algorithm has lower time complexity while retaining the schedulability, task preemption, and task migration competitive to the existing optimal scheduling algorithms.