[GNNet challenge 2020] End of the evaluation phase and provisional ranking

Dear participants of the Graph Neural Networking challenge 2020, First of all, thank you very much again on behalf of the BNN organizing team for participating in this challenge. We hope you enjoyed it a lot. Also, we expect it was a good opportunity for some of you to get introduced to the topics of network modeling and Graph Neural Networks. Once the evaluation phase has finished, we are glad to announce a provisional ranking with all the teams that submitted solutions for the challenge. You can find it at this link: https://bnn.upc.edu/challenge2020 We are very happy to see that you have made a really active participation. For the top-5 teams, please expect a separate email with detailed instructions on how to prepare the required documentation and the code to reproduce your solutions. For your interest, from the BNN team we have also prepared a possible solution for this challenge. Particularly, we have implemented a GNN model that introduces the queue entity as part of the internal GNN architecture. This enables to effectively model the impact of various queuing policies on delay. For more information, we have posted a short paper describing the solution and including some evaluation results on other datasets than those used in the challenge (https://arxiv.org/abs/2010.06686). Best regards, José Suárez-Varela Barcelona Neural Networking center Universitat Politècnica de catalunya