Stability of Adaptive Distributed Real-TimeSystems with Dynamic Resource Management

Today's embedded distributed real-time systems, are exposed to large variations in resource usage due to complex software applications, sophisticated hardware platforms, and the impact of their run-time environment. As eciency becomes more important, the applications running on these systems are extended with on-line resource managers whose job is to adapt the system in the face of such variations. Distributed systems are often heterogeneous, meaning that the hardware platform consists of computing nodes with dierent performance, operating systems, and scheduling policies, linked through one or more networks using dierent protocols. In this thesis we explore whether resource managers used in such distributed embedded systems are stable, meaning that the system's resource usage is controlled under all possible run-time scenarios. Stability implies a bounded worst-case behavior of the system and can be linked with classic real-time systems' properties such as bounded response times for the software applications. In the case of distributed systems, the stability problem is particularly hard because software applications distributed over the dierent resources generate complex, cyclic dependencies between the resources, that need to be taken into account. In this thesis we develop a detailed mathematical model of an adaptive, distributed real-time system and we derive conditions that, if satised, guarantee its stability