Andreas Johnsson

Factors Influencing LSTM Model Generalizability for IoT Intrusion Detection

Kaveh, Amin; Wassberg, Noah; Rohner, Christian; Johnsson, Andreas

Part of 2025 IEEE 11TH INTERNATIONAL CONFERENCE ON NETWORK SOFTWARIZATION, NETSOFT, p. 537-545, 2025

• DOI for Factors Influencing LSTM Model Generalizability for IoT Intrusion Detection

Meta Learning for Improved Policy Transfer in Changing Network Environments

Damberg, Simon; Larsson, Hannes; Johnsson, Andreas

Part of 2025 IEEE 11TH INTERNATIONAL CONFERENCE ON NETWORK SOFTWARIZATION, NETSOFT, p. 508-512, 2025

• DOI for Meta Learning for Improved Policy Transfer in Changing Network Environments

Congruent Learning for Self-Regulated Federated Learning in 6G

Taghia, Jalil; Moradi, Farnaz; Larsson, Hannes; Lan, Xiaoyu et al.

Part of IEEE TRANSACTIONS ON MACHINE LEARNING IN COMMUNICATIONS AND NETWORKING, p. 129-149, 2024

• DOI for Congruent Learning for Self-Regulated Federated Learning in 6G
• Download full text (pdf) of Congruent Learning for Self-Regulated Federated Learning in 6G

On Multi-Objective Neural Architecture Search for Modeling Network Performance

Orucu, Adam; Moradi, Farnaz; Ehrahimi, Masoumeh; Johnsson, Andreas

Part of 2024 15th International Conference on Network of the Future, NoF 2024, p. 214-218, 2024

• DOI for On Multi-Objective Neural Architecture Search for Modeling Network Performance

Impact of Attack Variations and Topology on IoT Intrusion Detection Model Generalizability

Kaveh, Amin; Rohner, Christian; Johnsson, Andreas

Part of 2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS), p. 364-370, 2024

• DOI for Impact of Attack Variations and Topology on IoT Intrusion Detection Model Generalizability

Congruent Learning for Self-Regulated Federated Learning in 6G

Taghia, Jalil; Moradi, Farnaz; Larsson, Hannes; Lan, Xiaoyu et al.

Part of IEEE TRANSACTIONS ON MACHINE LEARNING IN COMMUNICATIONS AND NETWORKING, p. 129-149, 2024

• DOI for Congruent Learning for Self-Regulated Federated Learning in 6G
• Download full text (pdf) of Congruent Learning for Self-Regulated Federated Learning in 6G

Change Point Detection with Adaptive Measurement Schedules for Network Performance Verification

Lindståhl, Simon; Proutiere, Alexandre; Johnsson, Andreas

Part of Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2023

• DOI for Change Point Detection with Adaptive Measurement Schedules for Network Performance Verification

Factors Influencing LSTM Model Generalizability for IoT Intrusion Detection

Kaveh, Amin; Wassberg, Noah; Rohner, Christian; Johnsson, Andreas

Part of 2025 IEEE 11TH INTERNATIONAL CONFERENCE ON NETWORK SOFTWARIZATION, NETSOFT, p. 537-545, 2025

• DOI for Factors Influencing LSTM Model Generalizability for IoT Intrusion Detection

Meta Learning for Improved Policy Transfer in Changing Network Environments

Damberg, Simon; Larsson, Hannes; Johnsson, Andreas

Part of 2025 IEEE 11TH INTERNATIONAL CONFERENCE ON NETWORK SOFTWARIZATION, NETSOFT, p. 508-512, 2025

• DOI for Meta Learning for Improved Policy Transfer in Changing Network Environments

On Multi-Objective Neural Architecture Search for Modeling Network Performance

Orucu, Adam; Moradi, Farnaz; Ehrahimi, Masoumeh; Johnsson, Andreas

Part of 2024 15th International Conference on Network of the Future, NoF 2024, p. 214-218, 2024

• DOI for On Multi-Objective Neural Architecture Search for Modeling Network Performance

Impact of Attack Variations and Topology on IoT Intrusion Detection Model Generalizability

Kaveh, Amin; Rohner, Christian; Johnsson, Andreas

Part of 2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS), p. 364-370, 2024

• DOI for Impact of Attack Variations and Topology on IoT Intrusion Detection Model Generalizability

Generalizable One-Way Delay Prediction Models for Heterogeneous UEs in 5G Networks

Rao, Akhila; Riaz, Hassam; Zavodovski, Aleksandr; Mochaourab, Rami et al.

Part of NOMS 2024-2024 IEEE Network Operations and Management Symposium, 2024

• DOI for Generalizable One-Way Delay Prediction Models for Heterogeneous UEs in 5G Networks

Comparing Transfer Learning and Rollout for Policy Adaptation in a Changing Network Environment

Samani, Forough Shahab; Larsson, Hannes; Damberg, Simon; Johnsson, Andreas et al.

Part of NOMS 2024-2024 IEEE Network Operations and Management Symposium, 2024

• DOI for Comparing Transfer Learning and Rollout for Policy Adaptation in a Changing Network Environment

RoME-QCD: Robust and Measurement Efficient Quickest Change Detection in 5G Networks

Lindståhl, Simon; Proutiere, Alexandre; Johnsson, Andreas

Part of Proceedings of the 8Th Network Traffic Measurement and Analysis Conference, TMA 2024, p. 1-11, 2024

• DOI for RoME-QCD: Robust and Measurement Efficient Quickest Change Detection in 5G Networks

Prediction and Exposure of Delays from a Base Station Perspective in 5G and Beyond Networks

Rao, Akhila; Tarneberg, William; Fitzgerald, Emma; Corneo, Lorenzo et al.

Part of PROCEEDINGS OF THE 2022 ACM SIGCOMM 2022 WORKSHOP ON 5G AND BEYOND NETWORK MEASUREMENTS, MODELING, AND USE CASES, 5G-MEMU 2022, p. 8-14, 2022

• DOI for Prediction and Exposure of Delays from a Base Station Perspective in 5G and Beyond Networks

Exploring Approaches for Heterogeneous Transfer Learning in Dynamic Networks

Sanz, Fernando Garcia; Ebrahimi, Masoumeh; Johnsson, Andreas

Part of PROCEEDINGS OF THE IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2022, 2022

• DOI for Exploring Approaches for Heterogeneous Transfer Learning in Dynamic Networks

Demonstration of Policy-Induced Unsupervised Feature Selection in a 5G network

Taghia, Jalil; Moradi, Farnaz; Larsson, Hannes; Lan, Xiaoyu et al.

Part of IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2022

• DOI for Demonstration of Policy-Induced Unsupervised Feature Selection in a 5G network

Measurement-based Admission Control in Sliced Networks: A Best Arm Identification Approach

Lindståhl, Simon; Proutiere, Alexandre; Johnsson, Andreas

Part of GLOBECOM 2022, p. 1484-1490, 2022

• DOI for Measurement-based Admission Control in Sliced Networks: A Best Arm Identification Approach

Policy-Induced Unsupervised Feature Selection: A Networking Case Study

Taghia, Jalil; Moradi, Farnaz; Larsson, Hannes; Lan, Xiaoyu et al.

Part of IEEE Conference on Computer Communications (IEEE INFOCOM 2022), p. 750-759, 2022

• DOI for Policy-Induced Unsupervised Feature Selection: A Networking Case Study

Source Selection in Transfer Learning for Improved Service Performance Predictions

Larsson, Hannes; Taghia, Jalil; Moradi, Farnaz; Johnsson, Andreas

Part of 2021 IFIP Networking Conference and Workshops (IFIP Networking), 2021

• DOI for Source Selection in Transfer Learning for Improved Service Performance Predictions

On Heterogeneous Transfer Learning for Improved Network Service Performance Prediction

Sanz, Fernando Garcia; Ebrahimi, Masoumeh; Johnsson, Andreas

Part of 2021 IEEEGlobal Communications Conference (GLOBECOM), 2021

• DOI for On Heterogeneous Transfer Learning for Improved Network Service Performance Prediction

Decentralizing Computation with Edge Computing: Potential and Challenges

Zavodovski, Aleksandr; Corneo, Lorenzo; Johnsson, Andreas; Mohan, Nitinder et al.

Part of IWCI'21, p. 34-36, 2021

• DOI for Decentralizing Computation with Edge Computing: Potential and Challenges

Towards Source Selection in Transfer Learning for Cloud Performance Prediction

Larsson, Hannes; Taghia, Jalil; Moradi, Farnaz; Johnsson, Andreas

Part of 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), p. 599-603, 2021

Predicting Round-Trip Time Distributions in IoT Systems using Histogram Estimators

Flinta, Christofer; Yan, Wenqing; Johnsson, Andreas

Part of NOMS 2020 - PROCEEDINGS OF THE 2020 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2020, 2020

Predicting Round-Trip Time Distributions in IoT Systems using Histogram Estimators

Flinta, Christofer; Yan, Wenqing; Johnsson, Andreas

2020

• DOI for Predicting Round-Trip Time Distributions in IoT Systems using Histogram Estimators

Towards Intelligent Industry 4.0 5G Networks: A First Throughput and QoE Measurement Campaign

Tarneberg, William; Hamsis, Omar; Hedlund, John; Brunnström, Kjell et al.

Part of 2020 28th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2020, 2020

• DOI for Towards Intelligent Industry 4.0 5G Networks: A First Throughput and QoE Measurement Campaign

Machine-Learning Based Active Measurement Proxy for IoT Systems

Yan, Wenqing; Flinta, Christofer; Johnsson, Andreas

Part of 2019 IFIP/IEEE Symposium On Integrated Network And Service Management (IM), p. 198-206, 2019