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The introduction of sophisticated ADAS has given rise to lar ger and more complex automotive communication networks whose efficient (in effort) and optimal (in qua lity) design necessarily depends on automated network design techniques. Typically, these techniques ei ther (a) optimize communication routes based on topology-independent constraint systems that encode the i nclusion of each network component in the route of a message or (b) depend on a timeand memory-expensive enume ration of all possible transmission routes to identify the optimal route. In this paper, we propose a nov el approach which combines the advantages of these two strategies to enable an efficient exploration of th e routing search space: First, the given network is preprocessed to identify so-called proxy areasin which each pair of nodes can be connected by exactly one route. Contrary to network areas with a variety of different routing possibilities, proxy areas do not offer any room for optimization. We propose two approaches—both inte grable into existing constraint systems—which exploit the knowledge gathered on proxy areas to improve the exploration efficiency during the routing optimization process. Experimental results for two mainstream topologies of automotive networks give evidence that, compared to state-of-the-art routing optimization a pproaches, the proposed approaches (a) offer an exploration speedup of up to ×185, (b) deliver network designs of equal or higher quality, and (c) enable an automated design of significantly larger automotive system .

Variety-aware Routing Encoding for Efficient Design Space Exploration of Automotive Communication Networks