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In our previous work, we have introduced an adaptive hierarchical scheduling framework as a solution for composing dynamic real-time systems, i.e., systems where the CPU demand of their tasks are subjected to unknown and potentially drastic changes during run-time. The framework uses the PI controller which periodically adapts the system to the current load situation. The conventional PI controller despite simplicity and low CPU overhead, provides acceptable performance. However, increasing the pressure on the controller e.g, with an application consisting of multiple tasks with drastically oscillating execution times, degrades the performance of the PI controller. Therefore, in this paper we modify the structure of our adaptive framework by replacing the PI controller with a fuzzy controller to achieve better performance. Furthermore, we conduct a simulation based case study in which we compose dynamic tasks such as video decoder tasks with a set of static tasks into a single system, and we show that the new fuzzy controller outperforms our previous PI controller.

Component-based software systems with real-time requirements are often scheduled using processor reservation techniques. Such techniques have mainly evolved around hard real-time systems in which worst-case resource demands are considered for the reservations. In soft real-time systems, reserv- ing the processors based on the worst-case demands results in unnecessary over-allocations. In this paper, targeting soft real-time systems running on multiprocessor platforms, we focus on components for which processor demand varies during run-time. We propose a feedback scheduling frameworkwhere processor reservations are used for scheduling components. The reservation bandwidths as well as the reservation periods are adapted using MIMO LQR controllers. We provide an allocation mechanism for distributing components over processors. The proposed framework is implemented in the TrueTime simulation tool for system identification. We use a case study to investigate the performance of our framework in the simulation tool. Finally, the framework is implemented in the Linux kernel for practical evaluations. The evaluation results suggest that the framework can efficiently adapt the reservation parameters during run-time by imposing negligible overhead.

Complexity in the real-time embedded softwaredomain has been growing rapidly. The component-based softwaredevelopment approach facilitates the development process of suchsoftware systems by dividing a complex system into a numberof simpler components. Resource reservation techniques havebeen widely used for providing resources to real-time softwarecomponents. In this paper we target real-time components operatingon a distributed resource infrastructure. Furthermore,we target a class of software components which demonstratedynamic resource consumption behavior. A prime example ofsuch components is a multimedia software component. In thepaper, we present a framework supporting multi-resource endto-end resource reservations. We reserve resource bandwidths onboth processor resources as well as on the network resources. Theproposed framework utilizes a Multiple Input Multiple Output(MIMO) controller which adjusts the sizes of reservations trackingthe dynamic resource demands of the software components. Finally, we present a case study using a multimedia component todemonstrate the performance and efficiency of our framework.

The Multi Processor Periodic Resource (MPR) model has been proposed for modeling compositional real-time systems which run on a shared multi processor hardware. In this paper we extend the MPR model such that the execution of virtual processors (servers) is not assumed to be synchronized i.e., the servers can have different phases. We believe that relaxing the server synchronization requirement provides greater deal of compatibility for implementing such a compositional method on various hardware platforms. We derive the resource supply bound function of the extended MPR model using an algorithm. Furthermore, we suggest an approach to calculate an approximate supply bound function with lower computational complexity for systems where calculating their supply bound function is computationally expensive.

Component-based software development providesa modular approach to develop complex software systems. In the context of real-time systems, it is desirable to abstract the timing properties of software components using an interface foreach component. The timing properties of the whole system, composed of multiple components, is studied using the component interfaces. In this paper we focus on periodic interface models. In the case of components developed for single processor platforms, for examining the system schedulability, the interfaces can be regarded as periodic tasks. Thus, making it possible to use the conventional schedulability analyses for the system level schedulability test. In the case of components developed formultiprocessors, since interfaces may have utilization larger than 100 % of a single processor, it is not possible to directly use the component interfaces for the system schedulability test. There-fore, the interfaces have to be decomposed before performing thesystem level schedulability test. In this paper, we target the special case of partitioned EDF for scheduling the components integrated on a multiprocessor. Therefore, the system level schedulability test is equivalent to finding a feasible allocation of component interfaces on the multiprocessor. We propose two algorithms for allocating the multiprocessor periodic interfaces. In addition, we propose anorthogonal approach for developing component-based real-timesystems on multiprocessors in which components with utilizationmore than 100 % of a single processor are divided into smaller subcomponents before abstracting their interfaces. We show, through extensive evaluations, that our alternative approach significantly reduces the interface overhead.