activity
20142022
most citedScanning the IPv6 Internet: Towards a Comprehensive Hitlist

26 citations · 42 across the 3 of their papers we have counts for

collaborators

12 papers

cs.NI2024

Fast and Scalable Network Slicing by Integrating Deep Learning with Lagrangian Methods

Tianlun Hu, Qi Liao, Qiang Liu +2

Network slicing is a key technique in 5G and beyond for efficiently supporting diverse services. Many network slicing solutions rely on deep learning to manage complex and high-dim…

cs.NI2023

Real-Time Performance of OPC UA

Erkin Kirdan, Filip Rezabek, Nikolas Mülbauer +2

OPC UA is an industry-standard machine-to-machine communication protocol in the Industrial Internet of Things. It relies on time-sensitive networking to meet the real-time requirem…

cs.DC20231 cited

Multilayer Environment and Toolchain for Holistic NetwOrk Design and Analysis

Filip Rezabek, Kilian Glas, Richard von Seck +3

The recent developments and research in distributed ledger technologies and blockchain have contributed to the increasing adoption of distributed systems. To collect relevant insig…

cs.NI202310 cited

Packed to the Brim: Investigating the Impact of Highly Responsive Prefixes on Internet-wide Measurement Campaigns

Patrick Sattler, Johannes Zirngibl, Mattijs Jonker +3

Internet-wide scans are an important tool to evaluate the deployment of services. To enable large-scale application layer scans, a fast, stateless port scan (e.g., using ZMap) is o…

cs.NI202321 cited

QUIC on the Highway: Evaluating Performance on High-rate Links

Benedikt Jaeger, Johannes Zirngibl, Marcel Kempf +2

QUIC is a new protocol standardized in 2021 designed to improve on the widely used TCP / TLS stack. The main goal is to speed up web traffic via HTTP, but it is also used in other…

cs.NI2023

Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis

Wenxuan Ye, Chendi Qian, Xueli An +2

Integrating native AI support into the network architecture is an essential objective of 6G. Federated Learning (FL) emerges as a potential paradigm, facilitating decentralized AI…