DOI: 10.5281/zenodo.17255272
title: Network Digital Twin-Generated Dataset for Machine Learning-based Detection of Traffic Congestion Problems

description: Overview

This record contains a set of synthetic datasets generated for the analysis and detection of congestion problems in realistic virtualized networks. The dataset collects metrics obtained via SNMP from network elements, enabling the capture of detailed information on device operational status and performance. These data are essential for training machine learning models aimed at anticipating, detecting, and preventing congestion episodes.

To obtain this information without impacting the performance of the scenario, specific probes were deployed within the Network Digital Twin (NDT), capable of collecting metrics in a non-intrusive manner. In addition, data flows emulating congestion or degradation conditions were generated on the scenario, enriching the dataset and providing greater realism to the modeled situations.

To address this challenge, a Network Digital Twin (NDT) approach was employed to emulate realistic network conditions and traffic patterns, enabling the automated generation of labeled data suitable for advanced analysis and early detection of congestion problems.

Feature Set:

📌 General Information





Interfaces: list of monitored interfaces




Host Name: device name




Timestamp: time marker




Number of detected interfaces



📌 TCP Metrics





tcpOutRsts




tcpInSegs




tcpOutSegs




tcpPassiveOpens




tcpRetransSegs




tcpCurrEstab




tcpEstabResets




tcpActiveOpens



📌 UDP Metrics





udpInDatagrams




udpOutDatagrams




udpInErrors



📌 Per-Interface Metrics (suffixes: *.3, *.4, *.5, .6)





Traffic in bytes: ifInOctets, ifOutOctets




Traffic in packets: ifInUcastPkts, ifOutUcastPkts, ifInNUcastPkts, ifOutNUcastPkts




Discards: ifInDiscards, ifOutDiscards




Host statistics: hostInPkts, hostOutPkts




Errors and collisions: etherStatsCollisions, etherStatsCRCAlignErrors




Abnormal packets: etherStatsUndersizePkts, etherStatsOversizePkts, etherStatsFragments, etherStatsJabbers




Volume and distribution: etherStatsOctets, etherStatsPkts, etherStatsBroadcastPkts, etherStatsMulticastPkts



(each repeated per interface: .3, .4, .5, .6)

📌 Bandwidth Metrics per Interface





bw_rx and bw_tx (per interface .3, .4, .5, .6)



📌 Dataset Label





LABEL 0/1/2/3/4





Dataset Variations:




To accommodate diverse research needs and scenarios, the dataset is provided in the following variations. Traffic bandwidth ranges emulated are as follows:





Range 0: 1–10 Mbps




Range 1: 11–40 Mbps




Range 2: 41–70 Mbps




Range 3: 71–90 Mbps




Range 4: Greater than 91 Mbps








dataset_01_TC31_05062025_labeled_final.csv



The bandwidth range distribution is approximately homogeneous, with around 20% for each generated range (ranges 0, 1, 2, 3, and 4).



dataset_02_TC31_07062025_labeled_final.csv



The bandwidth range distribution is approximately homogeneous, with around 50% for each generated range (ranges 3 and 4)



dataset_03_TC31_10062025_labeled_final.csv



In this case, a higher proportion of ranges 0, 1, and 2 has been enforced, while ranges 3 and 4 are reserved for emulating specific bursts exceeding 91 Mbps, up to 180 Mbps.

For ranges 0, 1, 2, and 3, the duration is between 60 and 120 seconds, whereas for burst type 4, the duration ranges between 5 and 40 seconds.