The paper "Resource Allocation is All You Need: The Routing and Scheduling Problem in 6TiSCH Networks" has been accepted for presentation at the IEEE Wireless Communications and Networking Conference (WCNC) 2025.
In a collaboration between the Organic Computing and NETCOM research groups, a method was developed to maximize the number of latency-critical data flows in 6TiSCH networks.

Der Klimawandel ist eine der gro?en Herausforderungen des 21. Jahrhunderts. Die Wissenschaft stattet die Gesellschaft hierbei mit Wissen, Methoden und Technologien aus, um Probleme und Herausforderungen frühzeitig zu erkennen, zu verstehen und darauf besser reagieren zu k?nnen. Passend zu diesem Thema ver?ffentlicht die Universit?t am 15. November 2024 in der Süddeutschen Zeitung eine Sonderbeilage über ?Forschung als Frühwarnsystem“.

Für das Paper ?Fitting the Puzzle: Towards Source Traffic Modeling for Mobile Instant Messaging" ist Prof. Dr. Michael Seufert, Lehrstuhl für Vernetzte Eingebettete Systeme und Kommunikationssysteme, Fakult?t für Angewandte Informatik an der Universit?t Augsburg, gemeinsam mit einem Team der Julius-Maximilians-Universit?t Würzburg auf der 15. Internationalen “Conference on Network of the Future” mit dem Best-Paper-Award ausgezeichnet worden.

Today our paper “Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS” was presented at the 1st Workshop on Network Security Operations (NecSecOr). This paper examines the effectiveness and consensus of various explainable AI (XAI) methods in enhancing the interpretability of machine learning-based Network Intrusion Detection Systems (ML-NIDS), finding that while some methods align closely, others diverge, underscoring the need for careful selection to build trust in real-world cybersecurity applications.

Today our paper “Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks” got presented at the 20th International Conference on Network and Service Management (CSNM). This paper explores the use of Active Learning (AL) to enhance Machine Learning (ML) models in network monitoring by incorporating expert input, aiming to increase model trust, adaptability, and performance, with a comprehensive evaluation of uncertainty-based AL approaches across various datasets and scenarios.

Prof. Seufert was ranked in the prestigious Stanford/Elsevier Top 2% Scientists list for the fourth time in a row. This list includes the world's 100,000 highest ranked scientists, as well as the top 2% in each of 174 disciplines. The repeated listing of Prof. Seufert underlines the outstanding research at his chair and the 伟德国际_伟德国际1946$娱乐app游戏 of Augsburg.

Our latest research paper in ACM TOMM focuses on how video streaming systems can better utilize available bandwidth to provide users with an improved Quality of Experience (QoE).

Our paper “(Not) The Sum of Its Parts: Relating Individual Video and Browsing Stimuli to Web Session QoE” got presented at the 16th International Conference on Quality of Multimedia Experience (QoMEX). This paper investigates the Quality of Experience (QoE) in web sessions that combine both web browsing and video streaming stimuli, addressing the gap in understanding session-level QoE and proposing models to estimate it based on individual stimuli.

Unser Paper ?QoEXplainer: 伟德国际_伟德国际1946$娱乐app游戏iating Explainable Quality of Experience Models with Large Language Models“ wurde auf der 16th International Conference on Quality of Multimedia Experience (QoMEX) vorgestellt. Das Papier stellt QoEXplainer vor, ein Dashboard, das gro?e Sprachmodelle und die Verwendung von 伟德国际_伟德国际1946$娱乐app游戏iatoren verwendet, um erkl?rbare, datengesteuerte Quality of Experience (QoE) Modelle zu veranschaulichen und den Benutzern zu helfen, die Beziehungen zwischen den Modellen durch eine interaktive Chatbot-Schnittstelle zu verstehen.

Our paper “Sitting, Chatting, Waiting: Influence of Loading Times on Mobile Instant Messaging QoE” got presented at the 16th International Conference on Quality of Multimedia Experience (QoMEX). The paper examines the relationship between loading times and user experience (QoE) in mobile instant messaging applications and shows that longer loading times reduce user acceptance and satisfaction, although they do not directly influence QoE ratings.

Prof. Dr. Michael Seufert, Inhaber des Lehrstuhls für Vernetzte Eingebettete Systeme und Kommunikationssysteme, hat den diesj?hrigen CNOM Young Professional Award des Institute of Electrical and Electronics Engineers Communications Society Technical Committee on Network Operation and Management gewonnen.

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Our paper “HALIDS: a Hardware-Assisted Machine Learning IDS for in-Network Monitoring” was published in the 8th Network Traffic Measurement and Analysis (TMA) Conference.?The paper presents HALIDS, a prototype of a Machine Learning-driven Intrusion Detection System that enables network devices to autonomously make security decisions using in-band and off-band traffic analysis, ultimately aiming to enhance network security through faster processing and intelligent decision-making.