Time-Triggered Traffic Planning for Data Networks with Conflict Graphs

Traffic planning is the key enabler of time-triggered real-time communication in distributed systems, and it is known to be notoriously hard. Current approaches predominantly tackle the problem in the domain of the traffic planning problem, e.g., by formulating constraints on the transmission schedules for individual data streams, or the links used by the data streams. This results in a high degree of coupling of the configuration of an individual data stream and the global (network-wide) traffic configuration with detrimental effects on the scalability and runtime of the planning phase.In contrast, we present a configuration-conflict graph based approach, which solves the original traffic planning problem by searching an independent vertex set in the conflict graph. We show how to derive the configuration-conflict graph, and discuss the conceptual advantages of this approach. To show the practical advantages of the conflict-graph based traffic planning approach we additionally present a proof-of-concept implementation and evaluate it against a reference ILP-based implementation. In our evaluations, our proof-of-concept implementation of the conflict-graph based approach outperforms the reference ILP and is more memory efficient, making it a promising alternative to current constraint-based traffic planning approaches.