Multiprocessor Real-Time Scheduling with a Few Migrating Tasks

Algorithms based on semi-partitioned scheduling have been proposed as a viable alternative between the two extreme ones based on global and partitioned scheduling. In particular, allowing migration to occur only for few tasks which cannot be assigned to any individual processor, while most tasks are assigned to specific processors, considerably reduces the runtime overhead compared to global scheduling on the one hand, and improve both the schedulability and the system utilization factor compared to partitioned scheduling on the other hand. In this paper, we address the preemptive scheduling problem of hard real-time systems composed of sporadic constrained-deadline tasks upon identical multiprocessor platforms. We propose a new algorithm and a scheduling paradigm based on the concept of semi-partitioned scheduling with restricted migrations in which jobs are not allowed to migrate, but two subsequent jobs of a task can be assigned to different processors by following a periodic str...

We describe a new algorithm, called Quasi-Partitioned Scheduling (QPS), capable of scheduling any feasible system composed of independent implicit-deadline sporadic tasks on identical processors. QPS partitions the system tasks into subsets, each of which is either scheduled by EDF on a single processor or by a set of servers on two or more processors. More precisely, QPS uses an efficient scheme to switch between partitioned EDF and global-like scheduling rules in response to system load variation, providing dynamic adaptation in the system. Extensive simulation compares QPS favorably against related work, showing that it has very low preemption and migration overheads.

2011

Optimal multiprocessor real-time schedulers incur significant overhead for preemptions and migrations. We present RUN, an efficient scheduler that reduces the multiprocessor problem to a series of uniprocessor problems. RUN significantly outperforms existing optimal algorithms with an upper bound of O(log m) average preemptions per job on m processors (≤ than 3 per job in all of our simulated task sets) and reduces to Partitioned EDF whenever a proper partitioning is found.

IEEE Access

Multi-processor systems consist of more than one processor and are mostly used for computationally intensive applications. Real-time systems are those systems that require completing execution of tasks within a pre-defined deadline. Traditionally, multiprocessor systems are given attention in periodic models, where tasks are executed at regular intervals of time. Gradually, as maturity in multiprocessor design had increased; their usage has become very common for real-time systems to execute both periodic and aperiodic tasks. As the priority of aperiodic task is usually but not essentially greater than the priority of periodic task, they must be completed within the deadline. There is a lot of research works on multiprocessor systems with scheduling of periodic tasks, but the task scheduling is relatively remained unexplored for mixed workload of both periodic and aperiodic tasks. Moreover, higher energy consumption is another main issue in multiprocessor systems. Although it could be reduced by using energy aware scheduling technique, the response time of aperiodic tasks still increases. In the literature, various techniques were suggested to decrease the energy consumption of these systems. However, the study on reducing the response time of aperiodic tasks is limited. In this paper, we propose a scheduling technique that: (i) executes aperiodic tasks at full speed and migrates periodic tasks to other processors if their deadline is earlier than aperiodic tasks-reduces the response time; and (ii) executes aperiodic tasks with lower speed by identifying appropriate processor speed without affecting the response time-reduces energy consumption. Through simulations, we demonstrate the efficiency of the proposed algorithm and we show that our algorithm also outperforms the well-known Total Bandwidth Server (TBS) algorithm. INDEX TERMS real-time systems, multi-processor scheduling, energy consumption, performance, dynamic voltage and frequency scaling

2000

In this paper we present the utilization bound for Earliest Deadline First (EDF) scheduling on homogeneous multiprocessor systems with partitioning strategies. Assuming that tasks are pre-emptively scheduled on each processor according to the EDF algorithm, and allocated according to the First Fit (FF) heuristic, we prove that the worst-case achievable utilization is ¼ ´Ò · ½µ, where Ò is the number of processors. This bound is valid for arbitrary utilization factors. Moreover, if all the tasks have utilization factors under a value «, the previous bound is raised, and the new utilization bound considering « is calculated.