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network-traffic-transformer

Network Traffic Transformer to learn network dynamics from packet traces. Learn fundamental dynamics with pre-training and fine-tune to multiple applications.

https://github.com/siddhant-ray/network-traffic-transformer

Science Score: 67.0%

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    CITATION.cff file
    Found CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
    Links to: acm.org
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    Scientific vocabulary similarity
    Low similarity (11.5%) to scientific vocabulary

Keywords

network-simulator transfer-learning transformer
Last synced: 6 months ago · JSON representation ·

Repository

Network Traffic Transformer to learn network dynamics from packet traces. Learn fundamental dynamics with pre-training and fine-tune to multiple applications.

Basic Info
  • Host: GitHub
  • Owner: Siddhant-Ray
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 6.6 MB
Statistics
  • Stars: 22
  • Watchers: 1
  • Forks: 4
  • Open Issues: 0
  • Releases: 1
Topics
network-simulator transfer-learning transformer
Created almost 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Network Traffic Transformer (NTT)

This work was undertaken as part of my master thesis at ETH Zurich, from Feb 2022 to Aug 2022, titled Advancing packet-level traffic predictions with Transformers. We present a new transformer-based architecture, to learn network dynamics from packet traces.

We design a pre-training phase, where we learn fundamental network dynamics. Following this, we have a fine-tuning phase, on different network tasks, and demonstrate that pre-training well leads to generalization to multiple fine-tuning tasks.

Original proposal:

Supervisors:

Research Lab:

We redirect you to the following sections for further details.

NOTE 1:

The experiments conducted in this project are very involved. Understanding and reproducing them from just the code and comments alone will be quite hard, inspite of the instructions mentioned in the given README. For more detailed understanding, we invite you to read the thesis (direct link). You can also check out an overview on the presentation slides (direct link)

For any further questions or to discuss related research ideas, please feel free to contact me by email.

NOTE 2:

Some results from the thesis have been written as a paper titled A new hope for network model generalization and the same has been accepted for presentation at ACM HotNets 2022. The paper is now online and open-access, it can be accessed via the ACM Digital Library via this link, DOI is: 10.1145/3563766.3564104.

NOTE 3:

The thesis has now been published under the ETH Research collection, which is open access. It can be accessed from here (direct link)

Owner

  • Name: siddhantray
  • Login: Siddhant-Ray
  • Kind: user
  • Company: UChicago

PhD @ UChicago | MSc @ ETH Zurich | B.Tech @ VIT Vellore

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Network Traffic Transformer
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Siddhant
    family-names: Ray
    affiliation: ETH Zurich
    orcid: 'https://orcid.org/0000-0003-0265-2144'
    email: siddhant.r98@gmail.com
  - given-names: Alexander
    family-names: Dietmüller
    affiliation: ETH Zurich
    orcid: 'https://orcid.org/0000-0003-3769-3958'
    email: adietmue@ethz.ch
keywords:
  - Transformer
  - Packet-level modelling
license: MIT
version: '1.0'

GitHub Events

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  • Watch event: 4
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  • Watch event: 4

Issues and Pull Requests

Last synced: almost 2 years ago

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  • Total issues: 0
  • Total pull requests: 16
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  • Average time to close pull requests: about 1 hour
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  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 16
  • Bot issues: 0
  • Bot pull requests: 10
Past Year
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  • Pull requests: 0
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Top Authors
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  • dependabot[bot] (10)
  • Siddhant-Ray (6)
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dependencies (10)

Dependencies

workspace/requirements.txt pypi
  • Keras-Preprocessing ==1.1.2
  • Markdown ==3.3.6
  • Pillow ==9.1.1
  • PyYAML ==6.0
  • Werkzeug ==2.1.1
  • absl-py ==1.0.0
  • aiohttp ==3.8.1
  • aiosignal ==1.2.0
  • astunparse ==1.6.3
  • async-timeout ==4.0.2
  • attrs ==21.4.0
  • black ==22.8.0
  • cachetools ==5.0.0
  • certifi ==2021.10.8
  • charset-normalizer ==2.0.12
  • click ==8.1.3
  • colorama ==0.4.5
  • cycler ==0.11.0
  • docformatter ==1.5.0
  • einops ==0.4.1
  • flatbuffers ==1.12
  • fonttools ==4.33.3
  • frozenlist ==1.3.0
  • fsspec ==2022.3.0
  • future ==0.18.2
  • gast ==0.4.0
  • google-auth ==2.6.6
  • google-auth-oauthlib ==0.4.6
  • google-pasta ==0.2.0
  • grpcio ==1.44.0
  • h5py ==3.7.0
  • idna ==3.3
  • importlib-metadata ==4.11.3
  • isort ==5.10.1
  • joblib ==1.1.0
  • keras ==2.9.0
  • kiwisolver ==1.4.3
  • libclang ==14.0.1
  • mando ==0.6.4
  • matplotlib ==3.5.2
  • multidict ==6.0.2
  • mypy-extensions ==0.4.3
  • numpy ==1.22.3
  • oauthlib ==3.2.1
  • opt-einsum ==3.3.0
  • packaging ==21.3
  • pandas ==1.4.2
  • pathspec ==0.10.1
  • platformdirs ==2.5.2
  • protobuf ==3.19.5
  • pyDeprecate ==0.3.2
  • pyasn1 ==0.4.8
  • pyasn1-modules ==0.2.8
  • pyparsing ==3.0.8
  • python-dateutil ==2.8.2
  • pytorch-lightning ==1.6.1
  • pytz ==2022.1
  • radon ==5.1.0
  • requests ==2.27.1
  • requests-oauthlib ==1.3.1
  • rsa ==4.8
  • scikit-learn ==1.0.2
  • scipy ==1.8.1
  • seaborn ==0.11.2
  • six ==1.16.0
  • tbparse ==0.0.6
  • tensorboard ==2.9.1
  • tensorboard-data-server ==0.6.1
  • tensorboard-plugin-wit ==1.8.1
  • tensorflow ==2.9.1
  • tensorflow-estimator ==2.9.0
  • tensorflow-io-gcs-filesystem ==0.26.0
  • termcolor ==1.1.0
  • threadpoolctl ==3.1.0
  • tomli ==2.0.1
  • torch ==1.11.0
  • torchmetrics ==0.8.0
  • tqdm ==4.64.0
  • typing_extensions ==4.1.1
  • untokenize ==0.1.1
  • urllib3 ==1.26.9
  • wrapt ==1.14.1
  • yarl ==1.7.2
  • zipp ==3.8.0
.github/workflows/codeql-analysis.yml actions
  • actions/checkout v3 composite
  • github/codeql-action/analyze v2 composite
  • github/codeql-action/autobuild v2 composite
  • github/codeql-action/init v2 composite
workspace/Dockerfile docker
  • ubuntu latest build