Garbage Collection Scheduling of Aperiodic Tasks

In the previous work of garbage collection （GC） models, scheduling analysis was given based on an assumption that there were no aperiodic mutator tasks. However, it is not true in practical real-time systems. The GC algorithm which can schedule aperiodic tasks is proposed, and the variance of live memory is analyzed. In this algorithm, active tasks are deferred to be processed by GC until the states of tasks become inactive, and the saved sporadic server time can be used to schedule aperiodic tasks. Scheduling the sample task sets demonstrates that this algorithm in this paper can schedule aperiodic tasks and decrease GC work. Thus, the GC algorithm proposed is more flexible and portable.

End-to-End Utilization Control for Aperiodic Tasks in Distributed Real-Time Systems

An increasing number of DRTS （Distributed model. The key challenges of such DRTS are guaranteeing Real-Time Systems） are employing an end-to-end aperiodic task utilization on multiple processors to achieve overload protection, and meeting the end-to-end deadlines of aperiodic tasks. This paper proposes an end-to-end utilization control architecture and an IC-EAT （Integration Control for End-to-End Aperiodic Tasks） algorithm, which features a distributed feedback loop that dynamically enforces the desired utilization bound on multiple processors. IC-EAT integrates admission control with feedback control, which is able to dynamically determine the QoS （Quality of Service） of incoming tasks and guarantee the end-to-end deadlines of admitted tasks. Then an LQOCM （Linear Quadratic Optimal Control Model） is presented. Finally, experiments demonstrate that, for the end-to-end DRTS whose control matrix G falls into the stable region, the IC-EAT is convergent and stable. Moreover,it is capable of providing better QoS guarantees for end-to-end aperiodic tasks and improving the system throughput.

Overload problem research on aperiodic real-time tasks

In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.

Energy-Efficient Deterministic Fault-Tolerant Scheduling for Embedded Real-Time Systems

By combining fault-tolerance with power management, this paper developed a new method for aperiodic task set for the problem of task scheduling and voltage allocation in embedded real-time systems. The scbedulability of the system was analyzed through checkpointing and the energy saving was considered via dynamic voltage and frequency scaling. Simulation results showed that the proposed algorithm had better performance compared with the existing voltage allocation techniques. The proposed technique saves 51.5% energy over FT-Only and 19.9% over FT ＋ EC on average. Therefore, the proposed method was more appropriate for aperiodic tasks in embedded real-time systems.

Hybrid and dependent task scheduling algorithm for on-board system software

In order to solve the hybrid and dependent task scheduling and critical source allocation problems, a task scheduling algorithm has been developed by first presenting the tasks, and then describing the hybrid and dependent scheduling algorithm and deriving the predictable schedulability condition. The performance of this agorithm was evaluated through simulation, and it is concluded from the evaluation results that the hybrid task scheduling subalgorithm based on the comparison factor can be used to solve the problem of aperiodic task being blocked by periodic task in the traditional operating system for a very long time, which results in poor scheduling predictability; and the resource allocation subalgorithm based on schedulability analysis can be used to solve the problems of critical section conflict, ceiling blocking and priority inversion; and the scheduling algorithm is nearest optimal when the abortable critical section is 0.6.