Andreas Kassler
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View article: A Robust Scheduling of Cyclic Traffic for Integrated Wired and Wireless Time-Sensitive Networks
A Robust Scheduling of Cyclic Traffic for Integrated Wired and Wireless Time-Sensitive Networks Open
Time-Sensitive Networking (TSN) is a toolbox of technologies that enable deterministic communication over Ethernet. A key area has been TSN's time-aware traffic shaping (TAS), which supports stringent end-to-end latency and reliability req…
View article: Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting Open
Accurate spatiotemporal traffic forecasting is vital for intelligent resource management in 5G and beyond. However, conventional AI approaches often fail to capture the intricate spatial and temporal patterns that exist, due to e.g., the m…
View article: Smart manufacturing: MLOps-enabled event-driven architecture for enhanced control in steel production
Smart manufacturing: MLOps-enabled event-driven architecture for enhanced control in steel production Open
We explore a Digital Twin-Based Approach for Smart Manufacturing to improve Sustainability, Efficiency, and Cost-Effectiveness for a steel production plant. Our system is based on a micro-service edge-compute platform that ingests real-tim…
View article: P4-MTAGG - a Framework for Multi-Tenant P4 Network Devices
P4-MTAGG - a Framework for Multi-Tenant P4 Network Devices Open
The current P4 programmability model assumes that a P4 programmable device is owned and controlled by a single tenant. However, in typical NFV scenarios, support for multiple tenants is desirable. When each tenant may want to deploy their …
View article: Performance Impact of Nested Congestion Control on Transport-Layer Multipath Tunneling
Performance Impact of Nested Congestion Control on Transport-Layer Multipath Tunneling Open
Multipath wireless access aims to seamlessly aggregate multiple access networks to increase data rates and decrease latency. It is currently being standardized through the ATSSS architectural framework as part of the fifth-generation (5G) …
View article: Quantum Machine Learning in Climate Change and Sustainability: A Short Review
Quantum Machine Learning in Climate Change and Sustainability: A Short Review Open
Climate change and its impact on global sustainability are critical challenges, demanding innovative solutions that combine cutting-edge technologies and scientific insights. Quantum machine learning (QML) has emerged as a promising paradi…
View article: Evaluate Temporal and Spatio-Temporal Correlations for Different Prosumers Using Solar Power Generation Time Series Dataset
Evaluate Temporal and Spatio-Temporal Correlations for Different Prosumers Using Solar Power Generation Time Series Dataset Open
This study investigates the temporal and spatio-temporal correlations of solar power generation among different prosumers of Uppsala and Halmstad, Sweden. Using solar power generation data from seven prosumer in Uppsala and five in Halmsta…
View article: TSN Network Scheduling—Challenges and Approaches
TSN Network Scheduling—Challenges and Approaches Open
Time-Sensitive Networking (TSN) is a set of Ethernet standards aimed to improve determinism in packet delivery for converged networks. The main goal is to provide mechanisms that enable low and predictable transmission latency and high ava…
View article: Quantum Machine Learning in Climate Change and Sustainability: a Review
Quantum Machine Learning in Climate Change and Sustainability: a Review Open
Climate change and its impact on global sustainability are critical challenges, demanding innovative solutions that combine cutting-edge technologies and scientific insights. Quantum machine learning (QML) has emerged as a promising paradi…
View article: Intent Negotiation Framework for Intent-driven Service Management
Intent Negotiation Framework for Intent-driven Service Management Open
To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as intents. To fulfill the inte…
View article: DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks
DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks Open
Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role in optimizing energy scheduling and enabling more flexible and intelligent power grid systems. As a result, these systems allow power utility comp…
View article: DA-LSTM: A Dynamic Drift-Adaptive Learning Framework for Interval Load Forecasting with LSTM Networks
DA-LSTM: A Dynamic Drift-Adaptive Learning Framework for Interval Load Forecasting with LSTM Networks Open
Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role in optimizing energy scheduling and enabling more flexible and intelligent power grid systems. As a result, these systems allow power utility comp…
View article: AIDA—A holistic AI-driven networking and processing framework for industrial IoT applications
AIDA—A holistic AI-driven networking and processing framework for industrial IoT applications Open
Industry 4.0 is characterized by digitalized production facilities, where a large volume of sensors collect a vast amount of data that is used to increase the sustainability of the production by e.g. optimizing process parameters, reducing…
View article: Automated and Systematic Digital Twins Testing for Industrial Processes
Automated and Systematic Digital Twins Testing for Industrial Processes Open
Digital twins (DT) of industrial processes have become increasingly important. They aim to digitally represent the physical world to help evaluate, optimize, and predict physical processes and behaviors. Therefore, DT is a vital tool to im…
View article: Automated and Systematic Digital Twins Testing for Industrial Processes
Automated and Systematic Digital Twins Testing for Industrial Processes Open
Digital twins (DT) of industrial processes have become increasingly important. They aim to digitally represent the physical world to help evaluate, optimize, and predict physical processes and behaviors. Therefore, DT is a vital tool to im…
View article: Intent Negotiation Framework for Intent-driven Service Management
Intent Negotiation Framework for Intent-driven Service Management Open
To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as intents. To fulfill the inte…
View article: Intent Negotiation Framework for Intent-driven Service Management
Intent Negotiation Framework for Intent-driven Service Management Open
To automate network operations and compute ser- vices, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as intents. To fulfill the intents, closed …
View article: Intent Negotiation Framework for Intent-driven Service Management
Intent Negotiation Framework for Intent-driven Service Management Open
To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as intents. To fulfill the inte…
View article: IntOpt: In-band Network Telemetry optimization framework to monitor network slices using P4
IntOpt: In-band Network Telemetry optimization framework to monitor network slices using P4 Open
The emergence of Network Functions Virtualization (NFV) is being heralded as an enabler of the recent technologies such as 5G/6G, IoT and heterogeneous networks. Existing NFV monitoring frameworks either do not have the capabilities to exp…
View article: Using Deep Reinforcement Learning for Zero Defect Smart Forging
Using Deep Reinforcement Learning for Zero Defect Smart Forging Open
Defects during production may lead to material waste, which is a significant challenge for many companies as it reduces revenue and negatively impacts sustainability and the environment. An essential reason for material waste is a low degr…
View article: From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors
From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors Open
The dynamicity of real-world systems poses a significant challenge to deployed predictive machine learning (ML) models. Changes in the system on which the ML model has been trained may lead to performance degradation during the system's li…