基于多样性感知的路由编码的汽车通信网络有效设计空间探索

Fedor Smirnov, Behnaz Pourmohseni, M. Glaß, J. Teich
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引用次数: 3

摘要

先进的ADAS系统的引入导致了更大、更复杂的汽车通信网络的出现,其高效(在努力上)和最佳(在质量上)的设计必然依赖于自动化网络设计技术。通常,这些技术是(a)基于对消息路由中每个网络组件的包含进行编码的拓扑无关约束系统来优化通信路由,或者(b)依赖于所有可能传输路由的时间和内存昂贵的枚举比率来识别最佳路由。在本文中,我们提出了一种结合这两种策略的优点的新方法,以实现对路由搜索空间的有效探索:首先,对给定的网络进行预处理,以识别所谓的代理区域,其中每对节点可以通过恰好一条路由连接。与具有各种不同路由可能性的网络区域相反,代理区域不提供任何优化空间。我们提出了两种方法,都可以集成到现有的约束系统中,利用在代理区域上收集的知识来提高路由优化过程中的勘探效率。两种主流汽车网络拓扑的实验结果证明,与最先进的路由优化方法相比,所提出的方法(a)提供高达×185的探索加速,(b)提供相同或更高质量的网络设计,以及(c)实现更大汽车系统的自动化设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Variety-aware Routing Encoding for Efficient Design Space Exploration of Automotive Communication Networks
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 .
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