Optimizing Extensibility in Hard Real-Time Distributed Systems

We consider a set of control tasks that must be executed on distributed platforms so that end-to-end latencies are within deadlines. We investigate how to allocate tasks to nodes, pack signals to messages, allocate messages to buses, and assign priorities to tasks and messages, so that the design is robust with respect to changes in task requirements. The notion of extensibility is used to measure robustness. The extensibility metric measures how much the execution times of tasks can be increased without violating end-to-end deadlines. We optimize this metric by adopting a mathematical programming front-end followed by post-processing heuristics. The proposed algorithm as applied to industrial strength test cases shows its effectiveness in optimizing extensibility and a marked improvement in running time with respect to an approach based on randomized optimization.