Performance Preservation Using Servers for Predictable Execution and Integration

In real-time embedded systems the components and components integration must satisfy both functional correctness and extra-functional correctness, such as satisfying timing properties. Deploying multiple real-time components on a physical node poses timing problems in components´s integration. These timing problems during integration further effect predictability and reusability of real-time components. We propose a novel concept of runnable virtual node (RVN) whose interaction with the environment is bounded both by a functional and a temporal interface, and the validity of its internal temporal behaviour is preserved when integrated with other components or when reused in a new environment. Our realization of RVN exploits the latest techniques for hierarchical scheduling framework to achieve temporal isolation, and the principles from component-based software-engineering to achieve functional isolation. Proof-of-concept case studies executed on an AVR based 32-bit micro-controller demonstrates the preserving of real-time properties within components for predictable integration and reusability in a new environment without altering its temporal behaviour in both hierarchical scheduling and RVN contexts. We also take a step ahead towards expanding the performance preserving servers´ concept for multicore platform on which the scheduling of real-time tasks is inherently unpredictable due to the contention for shared physical memory and caches. It results in proposing and implementation of a novel type of server, called Multi-Resource Server (MRS) which controls the access to both CPU and memory bandwidth resources such that the execution of real-time tasks become predictable. The MRS provides temporal isolation both between tasks running on the same core, as well as, between tasks running on different cores. Further, we provide the schedulability analysis for MRS to provide predictable performance when composing multiple components on a shared multi-core platform.