Kdn-users October 2019

kdn-users@knowledgedefinednetworking.org

2 participants
3 discussions

by Nathan Sowatskey

Hi In the demo code, for example in: https://github.com/knowledgedefinednetworking/demo-routenet/blob/master/dem… A form of normalisation is applied: predictions = 0.54*preds + 0.37 This is consistent with the parse() function here: https://github.com/knowledgedefinednetworking/demo-routenet/blob/master/cod… if k == 'delay': features[k] = (features[k] - 0.37) / 0.54 if k == 'traffic': features[k] = (features[k] - 0.17) / 0.13 if k == 'link_capacity': features[k] = (features[k] - 25.0) / 40.0 There is another case here: https://github.com/knowledgedefinednetworking/network-modeling-GNN/blob/mas… if k == 'delay': features[k] = (tf.math.log(features[k]) + 1.78) / 0.93 if k == 'traffic': features[k] = (features[k] - 0.28) / 0.15 if k == 'jitter': features[k] = (features[k] - 1.5) / 1.5 if k == 'link_capacity': features[k] = (features[k] - 27.0) / 14.86 if k == 'queue_sizes': features[k] = (features[k] - 16.5) / 15.5 What is the basis for this normalisation and those specific constants please? Why does the normalisation in routenet_with_link_cap and routenet_with_forwarding_nodes differ? Many thanks Nathan

5 years, 10 months

GBN topology

by Nathan Sowatskey

Hi On this page: https://github.com/knowledgedefinednetworking/Unveiling-the-potential-of-GN… I have seen that there is this data set: http://knowledgedefinednetworking.org/data/GBN.zip It is described as having been used for evaluation, but I can’t find anything else that refers to it. Can anyone tell me more please? Many thanks Nathan

5 years, 11 months

Normalisation in the demo.ipynb incompatible with training code

by Nathan Sowatskey

Hi I have noted that the normalisation applied in the demo notebook here: https://github.com/knowledgedefinednetworking/demo-routenet/blob/master/dem… Does not apply the same normalisation as the code here: https://github.com/knowledgedefinednetworking/demo-routenet/blob/master/cod… Specifically, delay is not normalised in the demo notebook. The demo notebook loads a checkpoint from here: https://github.com/knowledgedefinednetworking/demo-routenet/tree/master/tra… <https://github.com/knowledgedefinednetworking/demo-routenet/tree/master/tra…> This model, then, was created without normalising the delay also. That implies that the code that was used to train that model is not the same code that is in the routenet_with_link_cap.py code at the link above. In simpler terms, the demo notebook prediction does not work if the delay is normalised as at routenet_with_link_cap.py#L85. So, the code for training given in this repository is not compatible with the demo notebook and the trained model used as an example. Regards Nathan

5 years, 12 months

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Kdn-users October 2019