Sensornet designers seek to maximize energy efficiency while maintaining acceptable Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown, and combinatorial explosion renders impossible any exhaustive search approach. Most work published to date employs seemingly arbitrary choices of protocol parameters, derived by informal judgement and limited trial and error experiments. This lack of rigour may lead to sub-optimal parameter selection and sub-optimal network behaviour, and may mask the real performance differences of dissimilar protocols. We describe a reusable engineering method to address this multi-dimensional optimization problem, based on sound engineering principles widely recognized and applied beyond Computer Science. We provide a mechanism with which to de-risk deployment of sensornets tuned within training environments, and evaluate the robustness of these tunings to changing environments. The mechanism is also useful for comparative evaluation of protocols within a fixed deployment context. © The Author 2009. Published by Oxford University Press on behalf of The British Computer Society.