Torsten Braun

• Prof. Dr.
• Managing Director at University of Bern

As a mature indoor positioning solution, fingerprint-based positioning has been widely applied. However, traditional fingerprint positioning schemes still face the problems of limited hidden spatial feature extraction ability and insufficient fingerprint calibration with unlabeled crowdsourcing data. In order to address the above problems, we refer...

Fifth-generation (5G) mobile networks are expected to support the dynamic provisioning of services with heterogeneous Quality of Service requirements through Network Slicing. However, the uncertainty in the resource requirements of the tenant's future Network Slice Requests raises the problem of how Network Slices can be admitted onto the mobile ne...

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 used to train driving models and object detection and classification over sensitive datasets to continuously imp...

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-independent identically distributed (non-IID), from geographically distributed clients can deteriorate the FL tra...

Federated Learning (FL) is widely applied in privacy-sensitive domains, such as healthcare, finance, and education, due to its privacy-preserving properties. However, implementing FL in dynamic wireless networks poses substantial communication challenges. Central to these challenges is the need for efficient communication strategies that can adapt...

Unmanned Aerial Vehicles (UAVs) will be part of last-mile 5G/6G networks and will support Internet of Things (IoT) and low latency services in Flying Edge Computing (FEC). UAVs will densely populate aerial space in smart cities, providing networking and computing to interactive and monitoring services to ground users. FEC is composed of one or a se...

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 have significant demands on memory, computation, and energy and raise challenges for integrating them with the...

With the fast development of location-based services, an ubiquitous indoor positioning approach with high accuracy and low calibration has become increasingly important. In this work, we target on a crowdsourcing approach with zero calibration effort based on visible light, magnetic field and WiFi to achieve sub-meter accuracy. We propose a CrowdFu...

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 domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture a...

The millimeter-wave (mmWave) spectrum has become a core of wireless communication, which has the advantages of richer spectrum resources, larger communication bandwidth and smaller spectrum interference. Human Activity Recognition (HAR) by mmWave Radar based on point cloud attracts significant attention due to its nature of privacy-preserving, whic...

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 architecture is a non-trivial task, which is why this work develops a layered network architecture consisting of several...

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, resource heterogeneity of IoT devices slows down the training of the global model due to the presence of slower de...

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 Traffic Management System (TMS), which intends to improve mobility, driving experience, and safety of drivers and pas...

Predicting user behavior is the cornerstone of intelligent services and applications for providing and optimizing services over mobile networks. In modern edge computing scenarios, contents and services will be ordered close to end-users and will be highly sensitive to user mobility. Deep Learning models have had significant success in performing p...

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 Traffic Management System (TMS), which intends to improve mobility, driving experience, and safety of drivers and pas...

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 to address significant challenges, such as higher mobile traffic volumes and increasing network operation cost...

Large Machine Learning (ML) models require considerable computing resources and raise challenges for integrating them with the decentralized operation of heterogeneous and resource-constrained Internet of Things (IoT) devices. Running ML tasks on the cloud can introduce network delay, throughput, and privacy concerns, whereas running ML tasks on Io...

In modern networks, edge computing will be responsible for processing and learning from the critical network-and user-generated data, such as wireless link usage, mobility information, application requests, and many others. The presence of Artificial Intelligence-based (AI) applications at the edge of the network will enable the network to predict...

Future mobile communication networks need Unmanned Aerial Vehicles as Base Stations (UAVasBSs) with the fast-moving and long-term hovering capabilities to guarantee consistent network performance. UAVasBSs help 5G/B5G mobile communication systems to rapidly recover from emergency situations and handle the instant traffic of the flash crowd. In this...

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 immutably, and the process of certification is often not transparent. We propose Veritaa, a distributed public key infr...

In modern 5G and Beyond (B5G) networks, thenumber of users and devices consuming highly-demanding ser-vices in terms of latency and throughput. Due to their highdynamicity and fine-grainess, such services must be supportedby a joint management and integration effort between tech-nologies such as Mobile Edge Computing (MEC), UnmannedAerial Vehicles...

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 their trips. These parameters play an important role in route recommendation systems, and most of the currently a...

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 via service deployment at the edge of the mobile network. However, current solutions to support MEC struggle t...

Traditional WiFi positioning relies on a predefined radio map, which is labor-intensive and time-consuming for professionals. Recently, crowdsourcing has emerged as a promising solution for facilitating WiFi positioning. To crowdsense a radio map, traces collected from normal users are merged to recover the original walking paths. In this work, we...

Next-generation networks are expected to provide higher data rates and ultra-low latency in support of demanding applications, such as virtual and augmented reality, robots and drones, etc. To meet these stringent requirements of applications, edge computing constitutes a central piece of the solution architecture wherein functional components of a...

Future mobile networks will enable the massive deployment of mobile multimedia applications anytime and anywhere. In this context, mobility management schemes, such as handover and proactive multimedia service migration, will be essential to improve network performance. In this article, we propose a proactive mobility management approach based on g...

Today the integrity of digital documents and the authenticity of their origin is often hard to verify. Existing Public Key Infrastructures (PKIs) are capable of certifying digital identities but do not provide solutions to immutably store signatures, and the process of certification is often not transparent. In this work we propose Veritaa, a Distr...

Floating Content (FC) is a communication paradigm to locally share ephemeral content without direct support from infrastructure. It is based on constraining the opportunistic replication of content in a way that strikes a balance between minimizing resource usage and maximizing content availability among the intended recipients. However, existing a...

The focus of this chapter is on communication (and partially, computing) solutions which allow satisfying demands from the immediate aftermath of a disaster until full restoration of pre-disaster communication infrastructure and services. As traffic demand might differ substantially from the one in the pre-disaster scenario, due to the specific nee...

Although many target applications in VANETs are information-centric, the performance of Named Data Networking (NDN) in vehicular ad-hoc networks is severely hampered by persistent network partitioning, typical of many vehicular scenarios. Existing approaches try to address this issue by relying on opportunistic communications. However, they leave o...

The widespread diffusion of Online Social Networks and Media (OSNEM) has generated a huge amount of users' personal data. As this data is often publicly available, users' privacy is at risk. To address this issue, users may control the release of their sensitive data on OSNEM. An example of data that users rarely publish is their location. Besides...

The majority of communication solutions for post-disaster areas rely on cellular infrastructure support. But disasters such as fires, floods, earthquakes, can disrupt communication network making its services unavailable. New portable antenna towers, as point-to-point radio communications , are a way to mitigate the communication when cellular infr...

Emerging self-driving vehicles are now capable of sensing the environment and performing autonomous operations, paving the way to a more efficient, safer, and greener transportation system. On the other hand, emerging technologies such as vehicle-to-everything communications, 5G, and edge computing can expand even more the potential of automated dr...

L-SCN is a two-layered Service-Centric Networking (SCN) architecture. The L-SCN design splits the network into domains and specifies communication protocols for service provider information propagation. Nodes in a domain receive substantial knowledge about the available resources (e.g., CPU, RAM) and available services within the domain, while the...

Vehicular traffic re-routing is 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 Traffic Management System, which intends to improve not only mobility but also driving experience and safety of drivers a...

Seamless outdoor-indoor positioning plays a critical role in many emerging applications, e.g., large-coverage user navigation in cities, smart buildings, and analytics of user spatial location big data. It is still challenging to construct a large-scale seamless outdoor-indoor positioning system due to the limited coverage of indoor positioning. In...

In this thesis, Vehicular Named-Data Networking (VNDN) refers tothe use of the Named-Data Networking communication model over VehicularAd-hoc Networks. With the aim of addressing the problems caused by mobility to efficiently support VNDN communications in highly mobile traffic scenarios, various contributions were proposed in the scope of this the...

In the immediate aftermath of nature-based disasters such as earthquakes, fires, or floods, have a clear vision of the situation and the population involved is of main priority for rescue operations—it is a matter of life and death. But these disaster events may cause malfunctions in communication services making the exchange information impossible...

Software-Defined Networking (SDN) is a promising approach to simplify the management of Wireless Sensor Networks (WSNs). Many SDN frameworks for WSNs have been proposed, while real-world testbeds to accelerate the development of SDN-based WSN applications are still rare. In this work, we propose SDNWisebed: an SDN-empowered WSN testbed management s...

This paper presents a new video delivery scheme in mobile networks using Multi-Access Edge Computing (MEC). Our goal is to improve the quality of video streaming experienced by the mobile video consumer. Our approach is based upon Dynamic Adaptive Streaming over HTTP. We present a novel algorithm, which uses information obtained from the Radio Netw...

Opportunistic communications are expected to play a crucial role in enabling context-aware vehicular services. A widely investigated opportunistic communication paradigm for storing a piece of content probabilistically in a geographical area is Floating Content (FC). A key issue in the practical deployment of FC is how to tune content replication a...

Positioning is envisioned as an essential enabler of future fifth generation (5G) mobile networks due to the massive number of use cases that would benefit from knowing users’ positions. In this work, we propose a particle filter-based reinforcement learning (PFRL) approach for the robust wireless indoor positioning system. Our algorithm integrates...

Indoor location awareness enables many location-based services, such as smart homes or smart offices. The huge amount of sensor data collected by nowadays’ smartphones provides a solid basis for applying advanced machine learning algorithms to derive the correlation between indoor locations and sensor measurements. The combination of multiple senso...

The advent of Online Social Networks (OSNs) has offered the opportunity to study the dynamics of information spread and influence propagation at a huge scale. Considerable research has focused on the social influence phenomenon and its impact on OSNs. Social influence plays a crucial role in shaping people behavior and affecting human decisions in...

Opportunistic communications are expected to playa crucial role in enabling context-aware vehicular services. A widely investigated opportunistic communication paradigm for storing a piece of content probabilistically in a geographica larea is Floating Content (FC). A key issue in the practical deployment of FC is how to tune content replication an...

Traffic management systems (TMS) are the key for dealing with mobility issues. Moreover, 5G and vehicular networking are expected to play an important role in supporting TMSs for providing a smarter, safer and faster transportation. In this way, several infrastructure-based TMSs have been proposed to improve vehicular traffic mobility. However, in...

Service-Centric Networking (SCN) is a Future In-ternet architecture extending ICN with support for services, in which addressing and routing centers around services. SCN provides session support, however, recovery mechanisms do not exist in SCN session management. Therefore, SCN sessions suffer from link and node failures. In this paper, we present...

Vehicular traffic rerouting is the key to provide better traffic mobility. However, taking into account just traffic-related information to recommend better routes for each vehicle is far from achieving the desired requirements of proper transportation management. In this way, context-aware and multi-objective rerouting approaches will play an impo...

In this paper, we propose PopNetCod, a popularity-based caching policy for network coding enabled Named Data Networking. PopNetCod is a distributed caching policy, in which each router measures the local popularity of the content objects by analyzing the requests that it receives. It then uses this information to decide which Data packets to cache...

The challenge of efficient point-to-point communication in meshed Wireless Sensor and Actuator Networks (WSANs) can be addressed by Software Defined Networking (SDN). In contrast to the traditional routing protocols for Wireless Sensor Networks (WSNs) that use distributed local information for routing decisions, SDN based routing protocols can acce...

Content dissemination in Vehicular Ad-hoc Networks (VANETs) has the potential to enable a myriad of applications, ranging from advertising, traffic and emergency warnings to infotainment. This variety in applications and services calls for mechanisms able to optimize content storing, retrieval and forwarding among vehicles, without jeopardizing net...

In Named Data Networking (NDN), there is a need for routing protocols to populate Forwarding Information Base (FIB) tables so that the Interest messages can be forwarded. To populate FIBs, clients and routers require some routing information. One method to obtain this information is that network nodes exchange routing information by each node adver...

In-network caching is a feature shared by all proposed Information Centric Networking (ICN) architectures as it is critical to achieving a more efficient retrieval of content. However, the default "cache everything everywhere" universal caching scheme has caused the emergence of several privacy threats. Timing attacks are one such privacy breach wh...

Smartphones are a key enabling technology in the Internet of Things (IoT) for gathering crowd-sensed data. However, collecting crowd-sensed data for research is not simple. Issues related to device heterogeneity, security, and privacy have prevented the rise of crowd-sensing platforms for scientific data collection. For this reason, we implemented...

Vehicular Networks (VN) enable the collaboration among vehicles and infrastructure to deliver network services, where usually value-added services are provided by cloud computing. In this context, fog computing can be deployed closer to the users to meet their needs with minimum help from the Internet infrastructure. Software Defined Networking (SD...

In this work, we propose MobiVNDN, a distributed framework for Vehicular Named-Data networking (VNDN) communications. MobiVNDN focuses on mitigating the degradation of communication performance caused by mobility and wireless communications in VNDN. MobiVNDN simultaneously addresses the effects of several problems including broadcast storms, messag...