Modeling Preemptive EDF and FP by Integer Variables

Abstract The design of any system can be modeled by an optimization problem, where a decision must be taken to maximize an overall utility function within some constraints (that can be physical, contractual, etc.). In hard real-time systems the constraints are specified by the deadlines that are set for the completion of tasks. However classic schedulability tests are formulated by algorithms that prevent a visualization of the feasible region of the designer choices. In this paper we formulate the EDF and FP exact schedulability conditions on a single processor through a combination of linear constraints. We believe that this alternate representation is better suited for optimization and can trigger the development of more effective design methodologies for real-time systems.

A framework for hierarchical scheduling on multiprocessors: from application requirements to run-time allocation

Hierarchical scheduling is a promising methodology for designing and deploying real-time applications, since it enables component-based design and analysis, and supports temporal isolation among competing applications. In hierarchical scheduling an application is described by means of a temporal interface. The designer faces the problem of how to derive the interface parameters so to make the application schedulable, at the same time minimizing the waste of computational resources. The problem is particularly relevant in multiprocessor systems, where it is not clear yet how the interface parameters influence the schedulability of the application and allocation on the physical platform. In this paper we present three novel contributions to hierarchical scheduling for multiprocessor systems. First, we propose the Bounded-Delay Multipartition (BDM), a new interface specification model that allows the designer to balance resource usage versus flexibility in selecting the virtual platform parameters. Second, we explore the schedulability region of a real-time application on top of a generic virtual platform, and derive the interface parameter. Finally, we propose Fluid Best-Fit, an algorithm that takes advantage of the extra degree of flexibility provided by the BDM to compute the virtual platform parameters and allocate it on the physical platform. The performance of the algorithm is evaluated by simulations

A Framework for Hierarchical Scheduling on Multiprocessors: From Application Requirements to Run-Time Allocation

Hierarchical scheduling is a promising methodology for designing and deploying real-time applications, since it enables component-based design and analysis, and supports temporal isolation among competing applications. In hierarchical scheduling an application is described by means of a temporal interface. The designer faces the problem of how to derive the interface parameters so to make the application schedulable, at the same time minimizing the waste of computational resources. The problem is particularly relevant in multiprocessor systems, where it is not clear yet how the interface parameters influence the schedulability of the application and allocation on the physical platform. In this paper we present three novel contributions to hierarchical scheduling for multiprocessor systems. First, we propose the Bounded-Delay Multipartition (BDM), a new interface specification model that allows the designer to balance resource usage versus flexibility in selecting the virtual platform parameters. Second, we explore the schedulability region of a real-time application on top of a generic virtual platform, and derive the interface parameter. Finally, we propose Fluid Best-Fit, an algorithm that takes advantage of the extra degree of flexibility provided by the BDM to compute the virtual platform parameters and allocate it on the physical platform. The performance of the algorithm is evaluated by simulations

Design and Implementation of Distributed Resource Management for Time Sensitive Applications

In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by the resource manager, and (b) the service level of each application (service-level adaptation), executed by each application independently. We provide conditions under which the distributed recursive scheme exhibits convergence to solutions of the centralized objective (i.e., fair allocations). Contrary to prior work on centralized optimization schemes, the proposed framework exhibits adaptivity and robustness to changes both in the number and nature of applications, while it assumes minimum information available to both applications and the resource manager. We finally validate our framework with simulations using the TrueTime toolbox in MATLAB/Simulink

The Space of EDF Feasible Deadlines

It is well known that the performance of computer controlled systems is heavily affected by delays and jitter occurring in the control loops, which are mainly caused by the interference introduced by other concurrent activities. A common approach adopted to reduce delay and jitter in periodic task systems is to decrease relative deadlines as much as possible, but without jeopardising the schedulability of the task set. In this paper, we formally characterise the region of admissible deadlines so that the system designer can appropriately select the desired values to maximise a given performance index defined over the task set. Finally we also provide a sufficient region of feasible deadlines which is proved to be convex