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The efficiency of network virtualization depends on the appropriate assignment of resources. The underlying problem, called virtual network embedding, has been much discussed in the literature, and many algorithms have been proposed, attempting to optimize the resource assignment in various respects. Evaluation of those algorithms requires a large number of randomly generated embedding scenarios. This paper presents a novel scenario generation approach and demonstrates how to produce scenarios with a guaranteed exact solution, thereby, facilitating better evaluation of embedding algorithms.