Multiprocessor Synchronization of Periodic Real-Time Tasks Using Dependency Graphs

When considering recurrent real-time tasks in multiprocessor systems, access to shared resources, via so-called critical sections, can jeopardize the schedulability of the system. The reason is that resource access is mutual exclusive and a task must finish its execution of the critical section before another task can access the same resource. Therefore, the problem of multiprocessor synchronization has been extensively studied since the 1990s, and a large number of multiprocessor resource sharing protocols have been developed and analyzed. Most protocols assume work-conserving scheduling algorithms which make it impossible to schedule task sets where a critical section of one task is longer than the relative deadline of another task that accesses the same resource. The only known exception to the work-conserving paradigm is the recently presented Dependency Graph Approach where the order in which tasks access a shared resource is not determined online, but based on a pre-computed dependency graph. Since the initial work only considers frame-based task systems, this paper extends the Dependency Graph Approach to periodic task systems. We point out the connection to the uniprocessor non-preemptive scheduling problem and exploit the related algorithms to construct dependency graphs for each resource. To schedule the derived dependency graphs, List scheduling is combined with an earliest-deadline-first heuristic. We evaluated the performance considering synthesized task sets under different configurations, where a significant improvement of the acceptance ratio compared to other resource sharing protocols is observed. Furthermore, to show the applicability in real-world systems, we detail the implementation in LITMUS
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and report the resulting scheduling overheads.