Professor
Dienstags und Donnerstags jeweils von 0900-1100
Explorative Journey on 5G and beyond – Dos and Don't’s . Interactive Session
Würzburg
Accelerating Transport Layer Multipath Packet Scheduling for 5G-ATSSS
Würzburg
Automated and Systematic Digital Twins Testing for Industrial Processes
Towards the optimal orchestration of steerable mmWave backhaul reconfiguration
In: Computer Networks vol. 205 pg. 108750.
ISSN: 13891286
DOI: 10.1016/j.comnet.2021.108750
Using Deep Reinforcement Learning for Zero Defect Smart Forging
IntOpt: In-band Network Telemetry optimization framework to monitor network slices using P4
In: Computer Networks vol. 216 pg. 109214.
ISSN: 13891286
DOI: 10.1016/j.comnet.2022.109214
MultiScaler: A Multi-Loop Auto-Scaling Approach for Cloud-Based Applications
In: IEEE Transactions on Cloud Computing vol. 10 pg. 2769-2786.
In-network Support for Packet Reordering for Multiaccess Transport Layer Tunneling
pg. 1-6.
IEEE
DOI: 10.23919/PEMWN56085.2022.9963814
From concept drift to model degradation: An overview on performance-aware drift detectors
In: Knowledge-Based Systems vol. 245 pg. 108632.
ISSN: 09507051
DOI: 10.1016/j.knosys.2022.108632
Robust and energy-efficient user association and traffic routing in B5G HetNets
In: Computer Networks vol. 217 pg. 109305.
ISSN: 13891286
DOI: 10.1016/j.comnet.2022.109305
Multi-Objective Genetic Algorithm for Fast Service Function Chain Reconfiguration
In: IEEE Transactions on Network and Service Management pg. 1-1.
ISSN: 1932-4537
DOI: 10.1109/TNSM.2022.3195820
Accelerating a Transport Layer Based 5G Multi-Access Proxy on SmartNIC
Hybrid P4 Programmable Pipelines for 5G gNodeB and User Plane Functions
In: IEEE Transactions on Mobile Computing pg. 1-18.
ISSN: 1536-1233
Impact of Clustering Methods on Machine Learning based Solar Power Prediction Models
Providing In-network Support to Coflow Scheduling
pg. 235-243.
IEEE
DOI: 10.1109/NetSoft51509.2021.9492530
Toward In-Network Event Detection and Filtering for Publish/Subscribe Communication Using Programmable Data Planes
In: IEEE Transactions on Network and Service Management vol. 18 pg. 415-428.
ISSN: 1932-4537
DOI: 10.1109/TNSM.2020.3040011
Integration of AI, IoT and Edge-Computing for Smart Microgrid Energy Management
pg. 1-6.
IEEE
DOI: 10.1109/EEEIC/ICPSEurope51590.2021.9584756
Quantifying Uncertainty for Predicting Renewable Energy Time Series Data Using Machine Learning
pg. 50.
MDPI Basel, Switzerland
DOI: 10.3390/engproc2021005050
PerfSim: A Performance Simulator for Cloud Native Microservice Chains
In: IEEE Transactions on Cloud Computing pg. 1-1.
Software-Defined Time Sensitive Networks Configuration and Management
pg. 124-128.
IEEE
DOI: 10.1109/NFV-SDN53031.2021.9665120
A Randomized Greedy Heuristic for Steerable Wireless Backhaul Reconfiguration
In: Electronics vol. 10 pg. 434.
DOI: 10.3390/electronics10040434
Revitalizing Industrial Networking with Programmable Data Planes
BNG-HAL: A Unified API for Disaggregated BNGs
pg. 116-119.
IEEE
DOI: 10.1109/NFV-SDN53031.2021.9665122
Service Function Chain Placement for Joint Cost and Latency Optimization
In: Mobile Networks and Applications vol. 25 pg. 2191-2205.
ISSN: 1383-469X
DOI: 10.1007/s11036-020-01661-w
Performance Benchmarking of Virtualized Network Functions to Correlate Key Performance Metrics with System Activity
pg. 73-81.
IEEE
DOI: 10.1109/NoF50125.2020.9249199
A Performance Modelling Approach for SLA-Aware Resource Recommendation in Cloud Native Network Functions . Best Student Paper Award
pg. 292-300.
IEEE
DOI: 10.1109/NetSoft48620.2020.9165482
On the Construction of Optimal Embedding Problems for Delay-Sensitive Service Function Chains
pg. 1-10.
Spitzenprofessur der HighTech Agenda
Intelligent Networks and Systems (Head)
Andreas J. Kassler is Professor of Computer Science at Deggendorf Institute of Technology, Germany (since 2023) and Karlstads Universitet, Karlstad, Sweden (since 2005). From 2003 to 2004, Dr. Andreas J. Kassler was Assistant Professor at the School of Computer Engineering, Nanyang Technological University, Singapore. At Degegndorf, he is leading the Intelligent Network and Systems Lab. He maintains an active research program in the fields of networking and cloud computing with main research focus on Software Defined Networking, Future Internet, Datacenter Networking and, Quality of Service.
Dr. Andreas J. Kassler received the Docent title (Habilitation) in Computer Science from Karlstads Universitet in 2007 and the Ph.D. degree in Computer Science from Universität Ulm, Germany, in 2002. He received the M. Sc. degree in Mathematics/Computer Science in 1995 from Universität Augsburg, Germany.
He is co-author of around 55 peer reviewed journal articles and book chapters, 195 peer reviewed conference and workshop publications, 7 European or international patents and 11 IETF and ISO standardization contributions. He is also co-editor of a book published in the LNCS book series of Springer. He is the area editor of the Elsevier Computer Networks Journal, served as a guest editor of a feature topic in EURASIP Wireless Communications and Networking Journal, and served as Associate Editor on the editorial boards of some refereed international journals, such as: Journal of Internet Engineering, International Journal On Advances in Networks and Services.