direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content


Below, you can find a list of research prototypes that we are currently working on or have worked on in the past. To learn more about the prototypes, visit the linked Github pages.


(LEO) Satellite Networks

Large low earth orbit (LEO) satellite networks such as SpaceX's Starlink constellation promise to deliver low-latency, high-bandwidth Internet access with global coverage. As an alternative to terrestrial fiber as a global Internet backbone, they could potentially serve billions of Internet-connected devices. Currently, operators of CDNs exploit the hierarchical topology of the Internet to place points-of-presence near users, yet this approach is no longer possible when the topology changes to a single, wide-area, converged access and backhaul network. This toolkit allows simulation of a CDN with PoPs in a large LEO satellite constellation, including four proposed PoP placement strategies.

Related Publications:

  • Edge (of the Earth) Replication: Optimizing Content Delivery in Large LEO Satellite Communication Networks (Pfandzelter et al. 2020) PDF
Simulation Toolkit 

(Distributed) GeoBroker

In the Internet of Things, the relevance of data often depends on the geographic context of data producers and consumers. Today’s data distribution services, however, mostly focus on data content and not on geo-context, which could help to reduce the dissemination of excess data in many IoT scenarios. We propose to use the geo-context information associated with devices to control data distribution. For this, we designed GeoBroker, a data distribution service that uses the location of things, as well as geofences for messages and subscriptions, to control data distribution. This way, we enable new IoT application scenarios while also increasing overall system efficiency for scenarios where geo-contexts matter by delivering only relevant messages.

Related publications:

  • DisGB: Using Geo-Context Information for Efficient Routing in Geo-Distributed Pub/Sub Systems PDF
  • GeoBroker: Leveraging Geo-Contexts for IoT Data Distribution (Hasenburg and Bermbach 2020) PDF
  • GeoBroker: A Pub/Sub Broker Considering Geo-Context Information (Hasenburg and Bermbach 2020) PDF
  • Towards Geo-Context Aware IoT Data Distribution (Hasenburg and Bermbach 2020) PDF
(Distributed) GeoBroker prototype
Software Impacts Fork
Distributed GeoBroker simulation

MQTT Broadcast Groups

Today, communication between IoT devices heavily relies on fog-based publish/subscribe (pub/sub) systems. Communicating via the cloud, however, results in a latency that is too high for many IoT applications. This project is about a fog-based pub/sub system that integrates edge resources to improve communication latency between end devices in proximity. To this end, geo-distributed MQTT compliant broker instances organize themselves in dynamically sized broadcast groups that are connected via a scale-able fog broker.

Related publication:

  • Managing Latency and Excess Data Dissemination in Fog-Based Publish/Subscribe Systems (Hasenburg et al. 2020) PDF
Extension of moquette that supports broadcast groups
A simulation of the broadcast group formation process


The Function-as-a-Service (FaaS) model is a great fit for data and event processing in the Internet of Things (IoT). Sending all data to a cloud-based FaaS platform, however, may cause performance and privacy issues. While these issues could be mitigated using edge computing, existing FaaS approaches, designed for the cloud, are too heavyweight to run on small, constrained edge nodes.

tinyFaaS is a new FaaS system that is specifically designed for edge environments and their unique challenges. It is lightweight enough to run on low-performance single machine edge nodes, provides a CoAP endpoint to support communication with low-power devices, and uses Docker containers to isolate tenants.

Related publications:

  • tinyFaaS: A Lightweight FaaS Platform for Edge Environments (Pfandzelter and Bermbach 2020) PDF
Main repository with the tinyFaaS prototype


Fog computing is an emerging computing paradigm that uses processing and storage capabilities located at the edge, in the cloud, and possibly in between. Testing fog applications, however, is hard since runtime infrastructures will typically be in use or may not exist, yet.

MockFog is a tool that can be used to emulate such infrastructures in the cloud. Developers can freely design emulated fog infrastructures and configure their performance characteristics.

With MockFog 2.0, developers can also manage application components and do experiment orchestration.

Related publications:

  • MockFog: Emulating Fog Computing Infrastructure in the Cloud (Hasenburg et al. 2019) PDF
MockFog 2.0 - the successor of MockFog and MockFogLight
Meta repository with a presentation and a demo video
MockFog Infrastructure as Code artifacts
MockFog Node Manager
MockFog Agent 
A lightweight version of MockFog without a visual interface


Fog application design is complex as it comprises not only the application architecture, but also the runtime infrastructure, and the deployment mapping from application modules to infrastructure machines. For each of these aspects, there is a variety of design options that all affect quality of service and cost of the resulting application. FogExplorer, is an interactive simulation tool for the QoS and cost evaluation of fog-based IoT applications already during the design phase.

Related publications:

  • Supporting the Evaluation of Fog-based IoT Applications during the Design Phase (Hasenburg et al. 2018) PDF
  • FogExplorer (Hasenburg et al. 2018) PDF
FogExplorer prototype


The combination of edge and cloud in the fog computing paradigm enables a new breed of data-intensive applications. These applications, however, have to face a number of fog-specific challenges which developers have to repetitively address for every single application.

FBase is a replication service specifically tailored to the needs of data-intensive fog applications that aims to ease or eliminate challenges caused by the highly distributed and heterogeneous environment fog applications operate in.

Related publications:

  • FBase: A Replication Service for Data-Intensive Fog Applications (Hasenburg and Bermbach 2019) PDF
  • Towards a Replication Service for Data-Intensive Fog Applications (Hasenburg and Bermbach 2020) PDF
Main repository with the FBase system
The FBase Naming Service
Common utility classes used by FBase and the FBase Naming Service
Example FBase setup that uses Vagrant and VirtualBox 


An increased modal share of bicycle traffic is a key mechanism to reduce emissions and solve traffic-related problems. However, a lack of (perceived) safety keeps people from using their bikes more frequently. To improve safety in bicycle traffic, city planners need an overview of accidents, near miss incidents and bike routes. 

Such information, however, is currently not available. In our platform called Simra, we collect data on bicycle routes and near miss incidents using smartphone-based crowdsourcing.
Related publications:

  • SimRa: Using Crowdsourcing to Identify Near Miss Hotspots in Bicycle Traffic (Karakaya et al. 2020) PDF


The SimRa app for Android
The SimRa app for iOS

The SimRa backend software

Result data from the SimRa project

Screenshots of both the iOS and Android app

Web application for visualizing the dataset

Benchmarking in CI/CD

Continuous integration and deployment are established paradigms in modern software engineering. Both intend to ensure the quality of software products and to automate the testing and release process. Today’s state of the art, however, focuses on functional tests or small microbenchmarks such as single method performance while the overall quality of service (QoS) is ignored. We want to extend these pipelines with an additional application benchmark step which ensures QoS requirements and prevents performance regressions. Our current focus is centered on the evaluation of individual microservices and microservice applications.

Our benchmark plugin analyzes results and detects the violation of fixed performance metrics (e.g., defined in SLAs), sudden significant performance fluctuations, and long lasting regression trends. Our openISBT tool to benchmark arbitrary REST microservices generates its workload based on interaction patterns and the openAPI interface description of the respective service(s).

Related publications:

  • Continuous Benchmarking: Using System Benchmarking in Build Pipelines (Grambow et al. 2019) PDF
  • Benchmarking Microservice Performance: A Pattern-based Approach (Grambow et al. 2020)
This Plugin analyzes benchmark results and decides whether the release fulfills predefined QoS goals
Universal benchmark tool for REST microservices


In public video surveillance, there is an inherent conflict between public safety goals and privacy needs of citizens. Generally, societies tend to decide on middleground solutions that sacrifice neither safety nor privacy goals completely.

Watchyourfac.es is a prototype that leverages the inherent geo-distribution of fog computing to preserve privacy of citizens while still supporting camera-based digital manhunts of law enforcement agencies.

Related publications:

  • Public Video Surveillance: Using the Fog to Increase Privacy (Grambow et al. 2018) PDF
Watchyourfac.es prototype

Predicted Infection Risk for Aerosol Transmission of SARS-CoV-2

For a joint publication of Technischen Universität Berlin, the Charité, the Robert-Koch-Institut, and a public health department in Berlin, we build a web tool that calculates the predicted infection risk for aerosol transmission of SARS-CoV-2.

The tool is available at https://hri-pira.github.io/.

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions