Scalable scheduling algorithm for real-time distributed systems

Scheduling real-time tasks in a distributed-memory multiprocessor is characterized as sequencing a set of tasks and assigning them to processors of the architecture. Real-time systems research has extensively investigated the sequencing dimension of the scheduling problem by extending uni-processor scheduling techniques to more complex architectures. We introduce a technique that uses an assignment-oriented representation to dynamically schedule real-time tasks on the processors of the system. The technique we propose, automatically controls and allocates the scheduling time, in order to minimize deadline violation of real-time tasks, due to the scheduling overhead. We evaluate this technique in the context of scheduling real-time transactions in a distributed database application which we implemented on an Intel Paragon distributed-memory multiprocessor. In this implementation, we compared the performance of our algorithm with another dynamic algorithm that uses a sequence-oriented representation. The results show interesting performance trade-offs among the candidate algorithms and validate our conjectures about scalability performance limitations of sequence-oriented representations. The results also show the effect of the mechanisms that our technique uses to control and allocate scheduling time.