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The Hierarchical Scheduling Framework (HSF) has been introduced to enable compositional schedulability analysis and execution of embedded software systems with real-time constraints. In this thesis, we consider a system consisting of a number of semi-independent components called subsystems, and these subsystems are allowed to share logical resources. The HSF provides CPU-time to the subsystems and it guarantees that the individual subsystems respect their allocated CPU budgets. However, if subsystems are allowed to share logical resources, extra complexity with respect to analysis and run-time mechanisms is introduced. In this thesis we address three issues related to hierarchical scheduling of semi-independent subsystems. In the first part, we investigate the feasibility of implementing the hierarchical scheduling framework in a commercial operating system, and we present the detailed figures of various key properties with respect to the overhead of the implementation.

In the second part, we studied the problem of supporting shared resources in a hierarchical scheduling framework and we propose two different solutions to support resource sharing. The first proposed solution is called SIRAP, a synchronization protocol for resource sharing in hierarchically scheduled open real-time systems, and the second solution is an enhanced overrun mechanism.

In the third part, we present a resource efficient approach to minimize system load (i.e., the collective CPU requirements to guarantee the schedulability of hierarchically scheduled subsystems). Our work is motivated from a tradeoff between reducing resource locking times and reducing system load. We formulate an optimization problem that determines the resource locking times of each individual subsystem with the goal of minimizing the system load subject to system schedulability. We present linear complexity algorithms to find an optimal solution to the problem, and we prove their correctness

In this thesis we propose techniques to simplify the integration of subsystems while minimizing the overall amount of CPU resources needed to guarantee the schedulability of real-time tasks. In addition, we provide solutions to the problem of allowing for the use of logical resources requiring mutual exclusion.

The contribution of the thesis is presented in three parts. In the first part, we propose a synchronization protocol, called SIRAP, to facilitate sharing of logical resources in a hierarchical scheduling framework. In addition, we extend an existing synchronization protocol, called HSRP, such that each subsystem can be developed independently. The performance of the proposed protocols is evaluated by extensive simulations. In the second part, we present an efficient schedulability analysis that exploits the lower scheduling overhead introduced by each of the proposed protocols. Finally, in the third part, we propose new methods and algorithms that find the optimal system parameters (e.g., optimal resource ceiling), that minimize the amount of CPU resources required to ensure schedulability, when using the proposed synchronization protocols in a hierarchical scheduling framework.

The motivation of this work comes from an emerging industrial trend in embedded software systems development to integrate multiple applications (subsystems) on a small number of processors. The purpose of this integration is to reduce the hardware related costs as well as the communication complexity between processors. In this setting a large number of industrial applications face the problem of preserving their real-time properties after their integration onto a single processor. In addition, temporal isolation between the applications during runtime may be required to prevent failure propagation between different applications.

Specifically, we propose a hierarchical scheduling framework that allows for a simplified integration of subsystems. The framework preserves the essential temporal characteristics of the subsystems, both when running in isolation as well as when they are integrated with other subsystems. In this thesis, we assume a model where a system consists of a number of subsystems. The subsystems can interact with each other using shared logical resources. The framework ensures that the individual subsystem respects its allocated share of the processor. The difficulty lies in allowing two or more subsystems to share logical resources, which introduces an additional complexity in the schedulability analysis and also increases the system load.