Software systems that rely on ad-hoc networks are becoming increasingly complex and increasingly prevalent. Some of these systems provide vital functionality to military operations, emergency services and disaster relief; such systems may have significant impact on the safety of people involved in those operations. It is therefore important that those networks support critical software requirements, including those for latency of packet transfer. If a network ceases to meet the software's requirements (e.g. due to a link failure) then engineers must be able to understand it well enough to reconfigure the network and restore it to a requirement-satisfying state. Given a complex network, it is difficult for a human to do this under time pressure. In this paper we present a search-based tool which takes a network defined using the Network Description Language (NDL), annotated with a set of network-hosted applications and a set of latency requirements between each. We then evolve variants of the network configuration which meet the requirements and are robust to single link failures. We use network calculus tools to get a fast, conservative evaluation of whether a given network meets its requirements. We demonstrate that this approach is viable, designs networks much faster than a human engineer could, and is superior to a random generate-and-test approach.
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