Dear Professor,
I’m Zeyu, a PhD student from UC Berkeley. I am really interested in your work related in Graph Neural Networks -based routing optimization. I am trying to repeat your experiment. However, the download speed from the URL(path ='/home/datasets/SIGCOMM/nsfnetbw/tfrecords/train/') is so slow. Could you please transfer the zip package via the e-mail? Thank you very much!
Another question is that what’s the difference between dataset v0 and dataset v1. I am a little confused. Could you please explain further? Thanks a lot!
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tjuzeyuluan
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tjuzeyuluan(a)163.com
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签名由网易邮箱大师定制
Dear Professors and Researchers,
My name is Jiajun Chen, and I am a graduate student at the Xiamen University, China. I am writing to enquire about the dataset "NetworkModelingDatasets" which could not be downloaded right now. And i am doing the searchers about improving the RouteNet model. At your convenience, would you please send me the dataset. It would be a great help for our works.
Thank you for your attention to this matter.
Sincerely,
Jiajun Chen
graduate student, Xiamen University
Hello,
I am Hong-Nam Quach from Chonnam National University, Korean.
I am master student of Computer Science.
I am into your project, I want to study about it.
I try to download your dataset but I can not connect to your website that you provide.
Please, show me how to download or provide for me another link to download Dataset.
I’m looking your forward.
Thank you so much!
Best Regard,
Hong-Nam Quach
Hi
The reference 18 in "Understanding the Modeling of Computer Network Delays using Neural Networks" points to the KDN site as the location of the code use:
http://knowledgedefinednetworking.org
I think that the section being referred to is labelled “Neural Nets:”, but I would like to confirm that please.
Many thanks
Nathan
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
Hi
The NSF net topology is, I think, represented in this diagram:
https://github.com/knowledgedefinednetworking/NetworkModelingDatasets/blob/…
The same network is also, I think, represented by the NED file in this compressed tar:
http://knowledgedefinednetworking.org/data/datasets_v0/nsfnet.tar.gz
That NED file is also here in my project:
https://github.com/Data-Science-Projects/demo-routenet/blob/master/tests/un…
In that NED file, I see these connections:
node2.port[2] <--> Channel10kbps <--> node5.port[0];
node4.port[1] <--> Channel40kbps <--> node5.port[1];
node5.port[2] <--> Channel10kbps <--> node12.port[0];
node5.port[3] <--> Channel10kbps <--> node13.port[0];
In my (refactored from original code) I have these values for the connections at https://github.com/Data-Science-Projects/demo-routenet/blob/master/src/rout…
[{0: 1, 1: 3, 2: 2}, {0: 0, 1: 2, 2: 7}, {0: 0, 1: 1, 2: 5}, {0: 0, 1: 4, 2: 8}, {0: 3, 1: 5, 2: 6}, {0: 2, 1: 4, 2: 12, 3: 13}, {0: 4, 1: 7}, {0: 1, 1: 6, 2: 10}, {0: 3, 1: 9, 2: 11}, {0: 8, 1: 10, 2: 12}, {0: 7, 1: 9, 2: 11, 3: 13}, {0: 8, 1: 10, 2: 12}, {0: 5, 1: 9, 2: 11}, {0: 5, 1: 10}]
Node 5 is: {0: 2, 1: 4, 2: 12, 3: 13}, which means node 5 is connected to nodes 2, 4, 12 and 13. In the diagram, node 5 is connected to 2, 4, 12 and 8.
Does anyone have any ideas as to where the discrepancy is coming from please?
Many thanks
Nathan