This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine learning model. This data was generated as a result of the work described in the paper, "O-RAN with Machine Learning in ns-3," by the authors Wesley Garey, Tanguy Ropitault, Richard Rouil, Evan Black, and Weichao Gao from the 2023 Workshop on ns-3 (WNS3 2023), that was June 28-29, 2023, in Arlington, VA, USA, and published by ACM, New York, NY, USA. This paper is accessible at https://doi.org/10.1145/3592149.3592157. This data set includes the data from "Figure 10: Simulation Results Comparing the Baseline with the Heuristic, Distance, and ML Approaches," "Figure 11: Simulation Results that Depict the Impact of Increasing the Link Delay of the E2 Interface," as well as the data set used to train the machine learning model that is discussed there.
About this Dataset
| Title | O-RAN with Machine Learning in ns-3 |
|---|---|
| Description | This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine learning model. This data was generated as a result of the work described in the paper, "O-RAN with Machine Learning in ns-3," by the authors Wesley Garey, Tanguy Ropitault, Richard Rouil, Evan Black, and Weichao Gao from the 2023 Workshop on ns-3 (WNS3 2023), that was June 28-29, 2023, in Arlington, VA, USA, and published by ACM, New York, NY, USA. This paper is accessible at https://doi.org/10.1145/3592149.3592157. This data set includes the data from "Figure 10: Simulation Results Comparing the Baseline with the Heuristic, Distance, and ML Approaches," "Figure 11: Simulation Results that Depict the Impact of Increasing the Link Delay of the E2 Interface," as well as the data set used to train the machine learning model that is discussed there. |
| Modified | 2023-02-14 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | O-RAN , ns-3 , LTE , ONNX , Mobile Networks , Modeling and Simulation , Machine Learning |
{
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"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "Wesley Garey"
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"landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2996",
"title": "O-RAN with Machine Learning in ns-3",
"description": "This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine learning model. This data was generated as a result of the work described in the paper, \"O-RAN with Machine Learning in ns-3,\" by the authors Wesley Garey, Tanguy Ropitault, Richard Rouil, Evan Black, and Weichao Gao from the 2023 Workshop on ns-3 (WNS3 2023), that was June 28-29, 2023, in Arlington, VA, USA, and published by ACM, New York, NY, USA. This paper is accessible at https:\/\/doi.org\/10.1145\/3592149.3592157. This data set includes the data from \"Figure 10: Simulation Results Comparing the Baseline with the Heuristic, Distance, and ML Approaches,\" \"Figure 11: Simulation Results that Depict the Impact of Increasing the Link Delay of the E2 Interface,\" as well as the data set used to train the machine learning model that is discussed there.",
"language": [
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"distribution": [
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"downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2996\/data.zip",
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"name": "National Institute of Standards and Technology"
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"theme": [
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