Richard Urunuela

STORM a simulation tool for real-time multiprocessor scheduling evaluation

The increasing complexity of the hardware multiprocessor architectures as well as of the real-time applications they support makes very difficult even impossible to apply the theoretical real-time multiprocessor scheduling results currently available. Thus, so as to be able to evaluate and compare real-time multiprocessor scheduling strategies on their schedulability performance as well as energy efficiency, we have preferred a simulation approach and are developing an open and flexible multiprocessor scheduling simulation and evaluation platform called STORM. This paper presents the simulator on which STORM relies and that is able to simulate accurately the behaviour of those (hardware and software) elements that act upon the performances of such systems.

Efficiency evaluation of overhead control heuristics in DP-Fair multiprocessor scheduling

A number of optimal algorithms exist for scheduling of periodic taskset with implicit deadlines in real-time multiprocessor systems. However, the practical facts reveal that the optimality is achieved at the cost of excessive scheduling points, migrations and preemptions. In [19], we proposed two heuristics to control the overhead for a class of non-work conserving global scheduling algorithms that combine fluid scheduling and deadline partitioning, while guaranteeing optimality. This paper gives some detailed simulation results along with description of the system to generate the data for the simulation. The given results show the basic strength of the heuristics and validate their efficiency.

Overhead Control Heuristics in Boundary Fair Real-Time Multiprocessor Scheduling

The optimal scheduling algorithms in real-time multiprocessor systems are considered impractical. This is mainly because of the overhead generated due to the frequent scheduling points, migrations and preemptions. The solution to this problem is either to propose new algorithms with less overhead or to improve the existing ones. In this article, some simple heuristics to control the overhead are proposed for a class of optimal algorithms known as Boundary Fair scheduling. The heuristics do not disturb the optimality of the original algorithms. This paper gives some detailed simulation results along with description of experimental conditions. The given results show the basic strength of the heuristics and validate their efficiency both for non-work-conserving and work-conserving systems.

Overhead Control in DP-Fair Work Conserving Real-Time Multiprocessor Scheduling

In real-time multiprocessor scheduling, the optimal global scheduling algorithms are criticized for excessive overhead due to the frequent scheduling points, migrations and preemptions. DP-Fair model is an optimal scheduling which combines the notion of fluid scheduling (ideal fairness) with deadline partitioning. It has lower number of scheduling points as compare to PFair which is the first optimal scheduling algorithm proposed for real-time multiprocessor systems. DP-Fair model exists both for non-work conserving as well as work conserving cases. In [14,15], we used some simple heuristics which lower the overhead by reducing the number of migrations and preemptions in the non-work conserving context. In this article, we show that the very same heuristics can be envisaged in case of work conserving scheduling, and we evaluate their efficiencies for lowering the overhead.