Torsten Braun
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View article: FLATWISE: Flow Latency and Throughput Aware Sensitive Routing for 6DoF VR Over SDN
FLATWISE: Flow Latency and Throughput Aware Sensitive Routing for 6DoF VR Over SDN Open
View article: Hierarchical Placement Learning for Network Slice Provisioning
Hierarchical Placement Learning for Network Slice Provisioning Open
In this work, we aim to address the challenge of slice provisioning in edge-based mobile networks. We propose a solution that learns a service function chain placement policy for Network Slice Requests, to maximize the request acceptance r…
View article: Lightweight Graph Neural Networks for Enhanced 5G NR Channel Estimation
Lightweight Graph Neural Networks for Enhanced 5G NR Channel Estimation Open
Effective channel estimation CE is critical for optimizing the performance of 5G New Radio NR systems particularly in dynamic environments where traditional methods struggle with complexity and adaptability This paper introduces GraphNet a…
View article: Deep Reinforcement Learning for Context-Aware Online Service Function Chain Deployment and Migration over 6G Networks
Deep Reinforcement Learning for Context-Aware Online Service Function Chain Deployment and Migration over 6G Networks Open
View article: Towards Virtual Mobility Support in a Federated Testbed for Wireless Sensor Networks
Towards Virtual Mobility Support in a Federated Testbed for Wireless Sensor Networks Open
We present a design that accommodates ‘virtual mobility’ in a wireless sensor network testbed. Virtually-mobile nodes can be physical, simulated or emulated, and virtual mobility for all three types is treated uniformly by embedding the no…
View article: A Distributed Aggregation Approach for Vehicular Federated Learning
A Distributed Aggregation Approach for Vehicular Federated Learning Open
Federated Learning (FL) has rapidly become a crucial paradigm for training Machine Learning (ML) models when datasets are spread across several devices without compromising the privacy of the data owners. In vehicular networks, FL can be u…
View article: DFL: Dynamic Federated Split Learning in Heterogeneous IoT
DFL: Dynamic Federated Split Learning in Heterogeneous IoT Open
Federated Learning (FL) in edge Internet of Things (IoT) environments is challenging due to the heterogeneous nature of the learning environment, mainly embodied in two aspects. Firstly, the statistically heterogeneous data, usually non-in…
View article: Fully dynamic reorder policies with deep reinforcement learning for multi-echelon inventory management
Fully dynamic reorder policies with deep reinforcement learning for multi-echelon inventory management Open
The operation of inventory systems plays an important role in the success of manufacturing companies, making it a highly relevant domain for optimization. In particular, the domain lends itself to being approached via Deep Reinforcement Le…
View article: TENET: Adaptive Service Chain Orchestrator for MEC-Enabled Low-Latency 6DoF Virtual Reality
TENET: Adaptive Service Chain Orchestrator for MEC-Enabled Low-Latency 6DoF Virtual Reality Open
The next generation of Virtual Reality (VR) applications is expected to provide advanced experiences through Six Degrees of Freedom (6DoF) content, which requires higher data rates and ultra-low latency. In this article, we refactor 6DoF V…
View article: Machine Learning-based Energy Optimisation in Smart City Internet of Things
Machine Learning-based Energy Optimisation in Smart City Internet of Things Open
The deployment of Internet of Things (IoT) temperature sensors in urban areas is essential for the monitoring and understanding of the thermal environment. However, accurate temperature measurements can be compromised by factors such as di…
View article: DISNET: Distributed Micro-Split Deep Learning in Heterogeneous Dynamic IoT
DISNET: Distributed Micro-Split Deep Learning in Heterogeneous Dynamic IoT Open
The key impediments to deploying deep neural networks (DNN) in IoT edge environments lie in the gap between the expensive DNN computation and the limited computing capability of IoT devices. Current state-of-the-art machine learning models…
View article: Machine Learning-based Energy Optimisation in Smart City Internet of Things
Machine Learning-based Energy Optimisation in Smart City Internet of Things Open
Dataset for the paper Machine Learning-based Energy Optimisation in Smart City Internet of Things accepted for publication at The First International Workshop on the Integration between Distributed Machine Learning and the Internet of Thin…
View article: Machine Learning-based Energy Optimisation in Smart City Internet of Things
Machine Learning-based Energy Optimisation in Smart City Internet of Things Open
Dataset for the paper Machine Learning-based Energy Optimisation in Smart City Internet of Things accepted for publication at The First International Workshop on the Integration between Distributed Machine Learning and the Internet of Thin…
View article: Service Provisioning in Edge-Cloud Continuum: Emerging Applications for Mobile Devices
Service Provisioning in Edge-Cloud Continuum: Emerging Applications for Mobile Devices Open
Disruptive applications for mobile devices can be enhanced by edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of dom…
View article: ARLCL: Anchor-free Ranging-Likelihood-based Cooperative Localization
ARLCL: Anchor-free Ranging-Likelihood-based Cooperative Localization Open
This *dataset (68440 files of approx. 30GB unzipped) includes all Bluetooth Low Energy (BLE) Received Signal Strength (RSS) samples used for the evaluation of the Anchor-free Ranging-Likelihood-based Cooperative Localization (ARLCL) method…
View article: ARLCL: Anchor-free Ranging-Likelihood-based Cooperative Localization
ARLCL: Anchor-free Ranging-Likelihood-based Cooperative Localization Open
This *dataset (68440 files of approx. 30GB unzipped) includes all Bluetooth Low Energy (BLE) Received Signal Strength (RSS) samples used for the evaluation of the Anchor-free Ranging-Likelihood-based Cooperative Localization (ARLCL) method…
View article: An Online Multi-dimensional Knapsack Approach for Slice Admission Control
An Online Multi-dimensional Knapsack Approach for Slice Admission Control Open
Network Slicing has emerged as a powerful technique to enable cost-effective, multi-tenant communications and services over a shared physical mobile network infrastructure. One major challenge of service provisioning in slice-enabled netwo…
View article: Multi-Echelon Inventory Optimization Using Deep Reinforcement Learning
Multi-Echelon Inventory Optimization Using Deep Reinforcement Learning Open
In this chapter, we provide an overview of inventory management within the pharmaceutical industry and how to model and optimize it. Inventory management is a highly relevant topic, as it causes high costs such as holding, shortage, and re…
View article: ARES: Adaptive Resource-Aware Split Learning for Internet of Things
ARES: Adaptive Resource-Aware Split Learning for Internet of Things Open
Distributed training of Machine Learning models in edge Internet of Things (IoT) environments is challenging because of three main points. First, resource-constrained devices have large training times and limited energy budget. Second, res…
View article: ICN With DHT Support in Mobile Networks
ICN With DHT Support in Mobile Networks Open
Information-Centric Network (ICN) architectures, such as Named Data Networking (NDN), can improve content delivery on the Internet by deploying in-network caching techniques. Replacing the entire established Internet with a novel architect…
View article: Towards a Personalized Multi-objective Vehicular Traffic Re-routing System
Towards a Personalized Multi-objective Vehicular Traffic Re-routing System Open
Vehicular traffic re-routing is the key to provide better vehicular mobility. However, considering just traffic-related information to recommend better routes for each vehicle is far from achieving the desired requirements of a good Traffi…
View article: Towards a Personalized Multi-objective Vehicular Traffic Re-routing System
Towards a Personalized Multi-objective Vehicular Traffic Re-routing System Open
Vehicular traffic re-routing is the key to provide better vehicular mobility. However, considering just traffic-related information to recommend better routes for each vehicle is far from achieving the desired requirements of a good Traffi…
View article: Toward a Live BBU Container Migration in Wireless Networks
Toward a Live BBU Container Migration in Wireless Networks Open
Cloud Radio Access Networks (Cloud-RANs) have recently emerged as a promising architecture to meet the increasing demands and expectations of future wireless networks. Such an architecture can enable dynamic and flexible network operations…
View article: Federated User Clustering for non-IID Federated Learning
Federated User Clustering for non-IID Federated Learning Open
Federated Learning (FL) is one of the leading learning paradigms for enabling a more significant presence of intelligent applications in networking considering highly distributed environments while preserving user privacy. However, FL has …
View article: Veritaa: A distributed public key infrastructure with signature store
Veritaa: A distributed public key infrastructure with signature store Open
Summary Today, the integrity and authenticity of digital documents and data are often hard to verify. Existing public key infrastructures (PKIs) are capable of certifying digital identities but do not provide solutions to store signatures …
View article: REACT: A solidarity-based elastic service resource reallocation strategy for Multi-access Edge Computing
REACT: A solidarity-based elastic service resource reallocation strategy for Multi-access Edge Computing Open
The Multi-access Edge Computing (MEC) paradigm promises to enhance network flexibility and scalability through resource virtualization. MEC allows telecom operators to fulfill the stringent and heterogeneous requirements of 5G applications…
View article: Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips
Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips Open
Millions of individuals rely on urban transportation every day to travel inside cities. However, it is not clear how route parameters (e.g., traffic conditions, waiting times) influence users when selecting a particular route option for th…
View article: Reinforcement-supported Artificial Neural Network-based Trajectory Prediction
Reinforcement-supported Artificial Neural Network-based Trajectory Prediction Open
With the advent of 5G, Beyond 5G, and 6G cellular networks, mobility prediction has become a crucial task to enable a wide range of services such as handover and resource management. Mobility predictors analyze users’ historical mobility d…
View article: Distributed and Federated Learning Optimization with Federated Clustering of IID-users
Distributed and Federated Learning Optimization with Federated Clustering of IID-users Open
Poster: Distributed and Federated Learning Optimization with Federated Clustering of IID-users
View article: Running Written Exams Online at Bern University amid the COVID-19 Pandemic
Running Written Exams Online at Bern University amid the COVID-19 Pandemic Open
The unprecedented challenges that the world faced during the Covid-19 pandemic, reached also the education community. Our research group, offering two lectures at the time, presents and discusses in this white paper, the decisions and acti…