Scheduling algorithms and timing analysis for hard real-time systems

Real-time systems are designed for applications in which response time is critical. As timing is a major property of such systems, proving timing correctness is of utter importance. To achieve this, a two-fold approach of timing analysis is traditionally involved: (i) worst-case execution time (WCET) analysis, which computes an upper bound on the execution time of a single job of a task running in isolation; and (ii) schedulability analysis using the WCET as the input, which determines whether multiple tasks are guaranteed to meet their deadlines. Formal models used for representing recurrent real-time tasks have traditionally been characterized by a collection of independent jobs that are released periodically. However, such a modeling may result in resource under-utilization in systems whose behaviors are not entirely periodic or independent. Examples are (i) multicore platforms where tasks share a communication fabric, like bus, for accesses to a shared memory beside processors; (ii) tasks with synchronization, where no two concurrent access to one shared resource are allowed to be in their critical section at the same time; and (iii) automotive systems, where tasks are linked to rotation (e.g., of the crankshaft, gears, or wheels). There, their activation rate is proportional to the angular velocity of a specific device. This dissertation presents multiple approaches towards designing scheduling algorithms and schedulability analysis for a variety of real-time systems with different characteristics. Specifically, we look at those design problems from the perspective of speedup factor — a metric that quantifies both the pessimism of the analysis and the non-optimality of the scheduling algorithm. The proposed solutions are shown promising by means of not only speedup factor but also extensive evaluations