Looking at the table of contents, it sounds quite interesting, but I find some bits missing. (Maybe due to 2012 date?) DC networks generally follow a spine-lea

Looking at the table of contents, it sounds quite interesting, but I find some bits missing. (Maybe due to 2012 date?) DC networks generally follow a spine-leaf design, have ToR switches. They are DAGs and trees. These are effectively ultrametric spaces, which have a lot of nice properties that can be exploited for optimization and ML (e.g. these are generally bipartite graphs, so belief revision is guaranteed to terminate). In the same vein, basic abstract algebra and group theory (i.e. symmetries) could be quite useful as well.