Ibrahim Abdul Rahman. Bachelorarbeitsantrittsvortrag bei Dr. Matthias Fischer. 27.08.2025, 14.00 Uhr, F2.419

Diese Arbeit untersucht und vergleicht drei etablierte Datenstrukturen – Quadtrees, Bounding Volume Hierarchies (BVH) und Uniform Grids – im Kontext der 2D-Kollisionserkennung. Ziel ist es, ihre Effizienz, Anpassungsfähigkeit und Skalierbarkeit in unterschiedlichen Anwendungsszenarien zu analysieren, etwa bei vielen kleinen oder wenigen großen Objekten. Dazu wird eine eigens in C++ entwickelte 2D-Spielplattform als Testumgebung eingesetzt, die präzise Messungen von Laufzeit und Speicherverbrauch ermöglicht. Die Experimente erlauben eine differenzierte Bewertung der Stärken und Schwächen der einzelnen Ansätze und zeigen gezielte Optimierungspotenziale auf. Die Ergebnisse liefern nicht nur wissenschaftliche Erkenntnisse, sondern auch praxisrelevante Empfehlungen zur Wahl geeigneter Datenstrukturen in Echtzeitanwendungen.

Priyanka Giri. 20.08.2025, 14.00 Uhr, online

This thesis presents a grid-based abstraction framework to optimize pathfinding in large-scale hybrid networks, where nodes operate over hybrid communication network. By mapping complex Unit Disk Graph (UDG) topologies to structured grid graphs, the study significantly reduces computational complexity while preserving essential connectivity. The work evaluates Dijkstra’s, Bellman-Ford, and A* algorithms using Python’s NetworkX, analyzing metrics such as path efficiency, computation time, scalability, and packet transmission success rate. Results show that the proposed approach enhances routing performance and scalability without compromising path quality, offering practical applications in vehicular networks, IoT systems, and large-scale wireless infrastructures.

Thilo Berger. Masterarbeitsantrittsvortrag. 06.08.2025, 14:30 Uhr, F2.419

The problem setting is the following: we have many nodes which are randomly distributed over some space and which are able to communicate with each other if they are in close proximity. These distributed communication cluster have to be separately connected via edges to enable global communication. Our goal is to minimize the resulting cost. My masterthesis aims to implement and compare different approaches for the resulting sub-problems.

Alexander Nickel. Masterarbeitsantrittsvortrag bei Dr. Matthias Fischer. 06.08.2025, 14:00 Uhr, F2.419

In dieser Arbeit soll ein Algorithmus entwickelt werden, der im Rahmen der folgenden Technologien und Hardware, die Renderingzeit (GPU Zeit) eines beliebigen Frames, einer beliebigen Szene, in einer beliebigen Anwendung auf einem beliebigen Computer abschätzt. Die Technologien, die untersucht werden, sind die Texturen Verarbeitung, Lichtberechnung, Schattenberechnung, Ray Tracing und Antialiasing. Diese Eigenschaften werden mithilfe der Grafik Engine Software Godot untersucht. Eine moderne und beliebte Open Source Grafik Engine neben Unreal Engine und Unity die Grafik-APIs wie Vulkan verwendet. Für die Untersuchung werden im ersten Schritt nur die Computer eingesetzt, die mir von der Arbeitsgruppe „Algorithmen und Komplexität“ bereitgestellt wurden. Des Weiteren werden die Technologien, die in meiner Bachelorarbeit „Entwicklung und Analyse von Formeln zur Abschätzung der Renderingzeit eines Frames“ untersucht wurden, mit untersucht. Hierbei handelt es sich um eine Formel, die mithilfe von Knoten, Dreiecken, Vertex-Buffer-Objects (VBOs) und Surfels eine Framezeit (GPU Zeit) abschätzen kann.

Henning Hillebrandt. 23.07.2025, 14:00 Uhr, F2.419

Computing Single-Source Shortest Paths (SSSP) is a fundamental problem in distributed computing and an important building block for many distributed algorithms. In this talk, I present a new algorithm for solving the exact SSSP problem in the HYBRID network model. The algorithm computes exact shortest paths in weighted, directed graphs in time Õ(n^(1/3)), with high probability, matching the best-known result by Censor-Hillel et al. [STACS '21] despite only needing a local capacity of λ = Θ(|E|/n^(1/3)). It builds upon the SSSP framework from Forster and Nanongkai [FOCS '18], which was originally designed for the CONGEST model. The result is obtained through an efficient HYBRID implementation of their generic SSSP algorithm. To this end, I show how to compute a (1+o(1))-approximate solution of the h-hop-limited k-Source-Shortest Paths problem in weighted, directed graphs in time Õ(k + h^(1/2)), with high probability.

Matthias Artmann. 02.04.2025, 14:15 Uhr, F2.419

In programmable matter, we consider a large number of tiny, primitive computational entities called particles that run distributed algorithms to control global properties of the particle structure. In this paper, we study the shape containment problem, where the particles are given a description of a shape S and have to find maximally scaled representations of S within their initial configuration. We use the geometric amoebot model for programmable matter with its reconfigurable circuit extension, which allows the instantaneous transmission of primitive signals on connected subsets of particles.
We first prove a lower runtime bound of Omega(sqrt(n)) synchronous rounds for the general problem, where n is the number of particles. Then, we construct the class of snowflake shapes and its subclass of star convex shapes, and present solutions for both. Let k be the maximum scale of the considered shape in a given amoebot structure. If the shape is star convex, we solve it within O(log^2 k) rounds. If it is a snowflake but not star convex, we solve it within O(sqrt(n) log n) rounds.
In this talk, I will give a brief overview of the shape containment problem and the construction of snowflake shapes.

Jannatul Baki Showmik. Masterarbeitsabschlussvortrag. 19.03.2025, 14:00 Uhr

This study investigates a way to enhance the efficiency and scalability of blockchain technology by integrating the median rule into the process of reaching consensus in a distributed system. The core of this research focuses on the development and evaluation of the (k, l)-median rule. It designed to optimize the consensus process by reducing data overhead and improving transaction processing speeds across blockchain networks. The study demonstrates that the median rule significantly decreases the operational load of traditional blockchain architectures. It presents a detailed examination of the extended and compact variations of the median rule improve data flow efficiency. Merkle hash forest can be used to prove that any specific transaction has been executed. The findings suggest that enhancing blockchain systems with the median rule could lead to significant advancements in efficiency and make them more viable for extensive real-world applications.

Oliver Oster. Bachelorarbeitsabschlussvortrag. 04.12.2024, 14:00 Uhr

In this thesis we define a supervised distributed peer-to-peer system and implement it using services offered by the cloud service provider AWS. After laying out the foundations of the proposed system and the concepts used for its implementation, every component is deployed in AWS for simulations of two presented algorithm executed within the supervised distributed peer-to-peer system. The results are evaluated and a conclusion is drawn founded on the results of the simulations and the insights gathered during the development and writing process of this thesis.

Anna Dröge. Bachelorarbeitsabschlussvortrag. 27.11.2024, 14:00 Uhr

This thesis will analyse the dispersion of a swarm of N autonomous robots on areas of the form of non-convex polygons without holes. The robots will act according to the model chosen by Schmidt [1] in his thesis: Thus, robots will operate according to the LUMINOUS model with the FSYNC model used as a scheduler. To cover the polygon, robots first will build a chain of stationary robots at a distance of 1 upon the boundary and second form a grid consisting of squares with side length 1 upon the bounded area. The formation of the grid will take place in parts, separately for each (ortho-)convex part of the polygon. The thesis includes a proof of the algorithms' correctness. Moreover, ideas are presented on how the algorithm can be adapted to similar scenarios.

Vineet Vasishta Eranki. Masterarbeitsabschlussvortrag bei Dr. Matthias Fischer. 20.11.2024, 14:00 Uhr

This thesis improves a three-dimensional pathfinding algorithm in virtual environments, achieving better performance and visual clarity. The pathfinding algorithm processes scenes in 3D space into a set of interconnected graphs and then uses iterative deepening A* to find the shortest path between the start node and the goal node. To improve the existing algorithm, five key enhancements are made. The first goal ensures that there is no path between the start and goal nodes when these nodes are placed in different disconnected graph components. The second goal uses a directed graph structure for traversal of a sloped terrain, which consists of both uphill and downhill movement for different agents like person, bicycle, car, and truck based on their movement constraints. The third goal evaluates different heuristic functions, including Manhattan, Chebyshev, Diagonal, and Euclidean distance, to determine the better heuristic to improve execution time and to find the shortest path. The fourth goal ensures that a visually appealing straight line path is found between the start and goal nodes. The fifth goal ensures that graphs are processed faster by using multithreading.

Paul Bergmann. Masterarbeitsabschlussvortrag. 06.11.2024, 14:00 Uhr

Programmable matter, a system of connected objects (robots) that collaboratively solve tasks, has promising potential applications from nano-scale surgeries to shape-chaining matter fulfilling all kinds of tasks. Currently, developing a general framework for the shape reconstruction of programmable matter is the main challenge from an algorithmic point of view. As an intermediate step during the shape reconstruction, it might be reasonable to transform the matter into a simple (hole-free) structure since this generally simplifies finding a tile that can be removed and placed in another spot without losing connectivity in the configuration. We present the first algorithm for building such simple structures inside the bounding box of the start configuration for dodecahedron tile programmable matter in the passive tile (hybrid) model of Hinnenthal et al. [HRS20]. The algorithms presented run with logarithmic memory depending on the number of tiles and O(n⁴) time or constant memory and four pebbles in O(n⁵) time, respectively.

Roja Raj. Masterarbeitsabschlussvortrag. 23.10.2024, 15:00 Uhr

We explore the amoebot model, a distributed computing framework for programmable matter, by extending the model to solve the hexagon shape formation problem in the connected system with immobilized and non-immobilized particles. We consider that immobilized particles cannot move but can communicate with neighboring particles, while non-immobilized particles can both move and communicate. The central objective is to combine all non-immobilized particles to form a hexagon while ensuring that it does not include or surround the immobilized particles. In this thesis, we propose the HEX-IM algorithm, which is structured into multiple phases that guide scattered non-immobilized particles to navigate successfully around the immobilized particles and form a hexagon while maintaining connectivity and alignment. This research provides insights into shape formation mechanisms within complex particle configurations and has potential applications in various felds such as medicine, material science, and robotics. This presentation gives an overview of the proposed algorithamic idea to solve the issues with an efficient solution.

Tristan Lippold. Bachelorarbeitsabschlussvortrag. 23.09.2024, 14:00 Uhr

For a graph G a subset of edges M is called a matching if no two edges in M share a common vertex. A matching M is called a maximum matching if ∄ matching M':M'>M. In this paper a supervised peer-to-peer algorithm for finding a maximum matching in a general graph is presented. Furthermore, methods will be introduced to handle adversarial behaviour from a certain fraction of adversarial peers. Although the total work of the algorithm is in On5logn, the span of the task graph lies in Onlogn and is therefore promising. In addition, first ideas for converting the supervised peer-to-peer algorithm into a peer-to-peer algorithm will be described.

William Lepp. Bachelorarbeitsabschlussvortrag. 21.08.2024, 14:00 Uhr

In this talk, the three cryptocurrencies Bitcoin, Ethereum and Algorand will be compared. After an illustration of the so-called double-spending problem, a central problem for cryptocurrency, we will give a brief introduction to each of the three cryptocurrencies and show differences in how each system solves the double-spending problem.
As the double-spending problem is a consensus problem, we focus on the consensus mechanism used in each system.
Furthermore, we will compare the cryptocurrencies regarding their performance in terms of decentralization, scalability and security, also known as the blockchain trilemma. Finally, are comparison of the systems considering economic and ecological aspects will be presented.

Adarsch Manepalli. Masterarbeitsabschlussvortrag bei Dr. Matthias Fischer. 16.08.2024, 13:00 Uhr, F2.419

Data has become increasingly important in many scientific and technical domains, necessitating good administration and use strategies. This thesis proposes an innovative pipeline for automating tree species classification while generating realistic virtual landscapes using high-resolution satellite imagery and deep learning algorithms. The landscape of geospatial analysis and procedural content development has shifted substantially as technology has advanced. This study applies these breakthroughs to improve the realism and ecological accuracy of virtual environments. The proposed pipeline incorporates the Detectree2 package for precise tree crown delineation, utilizes custom CNN models and pre-trained backbone architectures for species classification, and employs a coordinate conversion process to translate classified tree locations into Unreal Engine for procedural tree placement. Challenges such as data acquisition limitations and computational demands are addressed. The pipeline’s potential applications are vast, including ecological studies, forest management, urban planning, and immersive visualization. This work advances geospatial analysis and procedural content generation, contributing an innovative approach to creating immersive and accurate virtual urban environments. This approach supports more precise and efficient analysis and visualization of forest ecosystems, paving the way for sustainable urban tree management and conservation efforts.

Natiq Sihab Akram. Masterarbeitsabschlussvortrag. 24.07.2024, 14:45 Uhr

This study presents a detailed examination of anomaly detection within N-Sensor data, aiming to enhance precision agriculture by refining field boundary delineation using machine learning techniques integrated with geospatial analysis. Focusing on Yara International’s N-Sensor and Varda’s Global Field ID system, this study addresses challenges posed by redundant data through spatial joins that effectively detect farm-relevant data points and remove non-farm points, significantly improving data accuracy. Machine learning limitations were encountered, notably a high rate of false negatives due to an imbalanced dataset for non-farm points. However, applying spatial joins offers a solution for removing non-farm points, optimizing data quality, and providing better computational efficiency. Consequently, this approach supports more accurate agricultural practices.

Gbadamosi Damiloda. Masterarbeitsabschlussvortrag bei Dr. Matthias Fischer. 24.07.2024, 14:00 Uhr

Path-finding algorithms are critical for developing interactive games, providing effective routes for characters to perform in virtual environments with complex scene structures. This thesis investigates the performance and suitability of three prominent path-finding algorithms: A*, Dijkstra, and Iterative Deepening A* (IDA*) which are practically applicable in a game prototype environment. This paper includes a study of six scenarios, each with difficult passages like obstacle blockages and complex terrain.

The introduction provides an in-depth explanation of the game mechanics and how the IDA* algorithm is combined with the iterative deepening procedure, demonstrating the role of the algorithm in path optimization. My strategy is to integrate the algorithms within the game layers, where significant aspects such as memory consumption, time performance, route length, and the appearance of smooth paths are considered. Visual explanation of the algorithm implementation is due to the screenshots of the coding process.

Scenario-delimited metrics from the evaluation give a detailed view of the scenarios' computational complexity. A* and Dijkstra algorithms can achieve consistently and reliably better performance as the algorithms enhance the adaptability of different gaming environments. On the other hand, IDA* demonstrates different efficiency levels when coping with scenario complexity, but there are unique improvements for the scenarios that embrace the IDA* iterative deepening strategy.

Moreover, another aspect of the analysis is the study of each algorithm's pros and cons. The advantages and disadvantages include the space and time complexity of each algorithm, heuristic function and limitations of the algorithms' optimization. The algorithm comparison reveals the usage of grid and octree in different scenes, making it easy for game developers to choose a suitable algorithm for their purpose.

The study's implications highlight the relevance of choosing algorithms according to the gaming system's environmental features. Developing an algorithm that will optimize the path-finding mechanisms and strike the right balance between computational effort and path-finding accuracy can be a task. This research is a step in the path-finding process in game development; it offers an elementary framework for further exploration and innovation in the design of interactive games.

Andreas Padalkin. 17.07.2024, 14:00 Uhr

In this talk, we study the computation of shortest paths within the geometric amoebot model, a commonly used model for programmable matter. Shortest paths are essential for various tasks and therefore have been heavily investigated in many different contexts. For example, in the programmable matter context, which is the focus of this paper, Kostitsyna et al. have utilized shortest path trees to transform one amoebot structure into another [DISC, 2023]. We consider the reconfigurable circuit extension of the model where this amoebot structure is able to interconnect amoebots by so-called circuits. These circuits permit the instantaneous transmission of simple signals between connected amoebots.

We propose two distributed algorithms for the shortest path forest problem where, given a set of k sources and a set of l destinations, the amoebot structure has to compute a forest that connects each destination to its closest source on a shortest path. For hole-free structures, the first algorithm constructs a shortest path tree for a single source within O(log l) rounds, and the second algorithm a shortest path forest for an arbitrary number of sources within O(log n log² k) rounds. The former algorithm also provides an O(1) rounds solution for the single pair shortest path problem (SPSP) and an O(log n) rounds solution for the single source shortest path problem (SSSP) since these problems are special cases of the considered problem.

Varun Maitreya Eranki. Masterarbeitsabschlussvortrag. 26.06.2024, 14:00 Uhr

In this thesis an exploration into the role of hardware and software combination for improving Byzantine Fault Tolerant State Machine systems with integration of novel Fever algorithm. The role of partial synchrony model in a consensus decision making, can improve the reliability and resiliency in the event of faults. Tolerance of such a system is explored practically in the presence of adversarial behaviour. An addition of cost effective precision clock overall improves the Fever algorithm.

Vincent Griebel. Bachelorarbeitsabschlussvortrag. 15.05.2024, 14:00 Uhr

Spätestens seit dem Bitcoin-Boom im Jahr 2020 haben Kryptowährungen die breite Öffentlichkeit erreicht. Doch obwohl einige Länder wie El Salvador Bitcoin sogar als offizielles Zahlungsmittel eingeführt haben, bleiben die Anwendungsmöglichkeiten eher limitiert. Gründe dafür lassen sich unter anderem in den Gegebenheiten des Bitcoin Protokolls finden. So ist die maximale Anzahl der Transaktionen auf zehn pro Minute beschränkt, und alle Transaktionsdaten sind öffentlich für jedermann zugänglich. Wie könnte man ein Zahlungsmittel schaffen, das einer Kryptowährung ähnelt, aber einige dieser Probleme löst?

In der Präsentation wird zuerst einmal Bitcoin analysiert, um zu verstehen, woher einige der Probleme kommen. Danach wird eine zentrale Blockchain konstruiert, welche keinen speziellen Konsensus Mechanismus benötigt. Zum Schluss wird noch betrachtet, wie die Beträge in Transaktionen so verschlüsselt werden können, sodass der Server die Transaktionen validieren, aber nichts weiteres über sie herausfinden kann.

Dominik Delgado Steuter. Bachelorarbeitsabschlussvortrag.Vincent Griebel. Bachelorarbeitsabschlussvortrag. 08.05.2024, 14:00 Uhr

What is the best way to make programs concurrent? How can threads be made more efficient and easier to use? In this paper, threads and the event model are compared for realizing concurrency in programs and opportunities for improvement of threads are presented. The microkernel seL4 is showcased and the threads it provides are implemented and analyzed regarding their ease of use and performance. Can they be improved? Also, a concurrency-optimal binary search tree is showcased and a partial implementation of it in the programming language C is discussed.

Matthias Artmann. Masterarbeitsabschlussvortrag. 24.04.2024, 14:00 Uhr, F2.419

Programmable matter is envisioned as a material that can alter its physical properties (shape, conductivity, appearance etc.) and react to external stimuli intelligently to fulfill a large variety of tasks in construction, maintenance, medicine and other application domains. Such materials are often imagined as large numbers of small computational entities, called particles, with very limited sensing, communication and movement abilities. By modeling programmable matter as distributed systems, we can study its theoretical capabilities and limitations under varying assumptions and independent of physical implementations.

The problem of shape formation, i.e., reorganizing an arbitrary initial configuration of particles into a desired shape, has been studied extensively in various models due to its high practical relevance. We consider the related problem of shape containment, where the particles have to find the maximum scale at which a given shape can be represented by the initial configuration (i.e., without movement) and identify a subset of particles representing the maximally scaled shape. A shape containment solution could serve as a preparation for fast shape formation algorithms or other complex procedures, but the problem has not been studied in the context of programmable matter so far. In this master's thesis, we present solutions to the shape containment problem in the amoebot model, using the model's reconfigurable circuits extension to enable fast communication over long distances. In addition to a solution of the most general problem case, we identify several classes of shapes and initial configurations with more efficient solutions, achieving sublinear runtimes in the number of particles. The final presentation of this thesis gives an overview of the considered problem cases and presents the key algorithmic ideas used to solve these cases efficiently.

Sebastian Korzeczek. Masterarbeitsabschlussvortrag. 17.04.2024, 14:00 Uhr, F2.419

In the shape formation problem, the goal is to transform an initial shape into a given target shape. The scale of the formed target shape is maximal with respect to the number of passive objects in the initial shape. Such an algorithm was formalized in the Amoebot Model with joint movements and partially implemented in the AmoebotSim2.0 simulation environment. The shape formation algorithm presented here is capable of forming the target shape in O(m²) rounds, where m is the number of passive objects in the initial shape.

Carsten de Groote. Masterarbeitsabschlussvortrag. 27. März 2024, 14:00 Uhr, F2.419

We present a simple algorithm for the dispersion of n robots. Robots are tasked with distributing themselves in order to cover an area by moving away from their nearest neighbour. With only small changes the algorithm is applicable to unbounded two-dimensional space, circle-, convex polygon- and non-convex polygon boundaries. In bounded areas P, we assume n = O(Area(P)).

The algorithm is based on the assumptions of the OBLOT robot model. The robots execute the same algorithm under the Look-Compute-Move model, they are indistinguishable from another, they have no means of communication or persistent memory across executions and act only based on their local surroundings. Furthermore, the local coordinate systems of the robots are not aligned and their chirality (sense of left and right) can vary.

We provide select results about the correctness and limitations of the provided algorithms as well as hypotheses about the algorithms quality. Results are supported by extensive simulations.

Rajesh Doddegowda. Masterarbeitsabschlussvortrag. 13. März 2024, 14:00 Uhr, F2.419

This thesis investigates a comparative analysis of heuristic algorithms and reinforcement learning for solving complex combinatorial optimization problems, particularly focusing on variants in drone-based delivery systems such as the Traveling Salesman Problem with Drones (TSP-D), the Multiple Drone Routing Problem (MDRP), and the Drone-Truck Routing Problem, using the Christofides algorithm. Recognizing the limitations inherent in basic algorithms when applied to these complex scenarios, the study proposes different heuristic methods, including the 2-opt heuristic, the Steady-state genetic algorithm, and the Christofides algorithm. Additionally, the thesis implements advanced reinforcement learning techniques, including attention-based encoder-decoder models and Long Short-Term Memory (LSTM) networks. The primary objective of this model is to enhance the coordination and routing efficiency of trucks and drones in logistics networks, taking into account critical factors like node probabilities, customer demands, and depot capacities. The thesis thoroughly tests and evaluates the efficiency, runtime, operational challenges, and cost implica- tions associated with these methods. It aims to identify an optimal balance between effectiveness and resource constraints, crucial in real-world logistics and delivery sce- narios. The findings highlight the adaptability of heuristic methods under varying conditions and underscore the potential of reinforcement learning for deeper and more complex analytical tasks. This thesis offers valuable insights into algorithm selection, tailored to the specificities of the problem and resource availability. It contributes significantly to the field by providing a comprehensive understanding of the strengths and limitations of both heuristic and reinforcement learning approaches in the context of modern, complex, and dynamic routing problems.

Gleb Polevoy. 28. Februar 2024, 14:00 Uhr, F2.419

People, robots, and companies mostly divide time and effort between projects, and shared effort games model people investing resources in public projects and sharing the generated values. In linear θ sharing (effort) games, a project’s value is linear in the total contribution, thus modelling predictable and scalable activities. The threshold θ for effort defines which contributors win and receive their share, equal share modelling standard salaries, equity-minded projects, etc. Thresholds between 0 and 1 model games such as paper co-authorship and shared assignments, where a minimum positive contribution is required for sharing in the value. We constructively characterise the conditions for the existence of a pure equilibrium for θ ∈ {0, 1}, and for two-player games with a general threshold, and find the prices of anarchy and stability. For more players, we also provide existence and efficiency results, and use generalised fictitious play simulations to show when a pure equilibrium exists and what its efficiency is. We propose a novel method for studying solution concepts by defining a new concept and proving its equivalence to a previously known on a large subclass of games. This means that the original concept narrows down to a more demanding concepts on certain games, providing new insights and opening a path to study both concepts conveniently. We also prove mixed equilibria always exist and bound their efficiency. This facilitates reaching socially efficient equilibria.

Jie Liu. Joint work with Gleb Polevoy. 21. Februar 2024, 14:00 Uhr, F2.419

When evaluating different Nash equilibrium profiles, there are several properties that are important to consider. The most important properties include Social Welfare, which measures the overall benefit to the entire group; Discrepancy, which refers to the difference of utilities of every player; and Uniqueness, which ensures that players will be certain which strategy to use. The strength of a solution concept is crucial as well. It reveals how likely a group of players might want to deviate. Consideration of these properties is essential for selecting an optimal equilibrium for a given game.
The current literature needs a comprehensive comparison integrating these key properties, to allow for an educated comparison and selection of solution concepts.
This gap hinders the full appreciation of the implications that each refinement may have on the aforementioned metrics. Our research thus aims to bridge this gap by finding the relationship between important properties of solution concepts.
In summary, we prove that there are interconnections between properties of Nash equilibria, some stands for general cases while others only apply to certain important classes of games.

Heena Thakur, Masterarbeitsabschlussvortrag. 14. Februar 2024, 14:00 Uhr, F2.419

Artificial Intelligence (AI) is becoming one of the fastest-growing technologies in the current time. It is being used in almost all fields like the IT sector, finance sector, education sector, etc. It is slowly becoming an integral part of our day-to-day lives. It is now also becoming increasingly useful in the field of Healthcare. AI finds many uses in the healthcare sector, these include, chat-based diagnosis, drug discovery, health monitoring, etc. But unlike other sectors, where major issues cause loss of money or reputations, any issue in the field of healthcare can lead to catastrophic effects since they directly impact human life. Loss of human life is the most dangerous loss which is why we need to ensure that AI is working to benefit humans and not harm them in any way. Thus, it becomes important to understand what AI is doing when it comes to the field of healthcare. Most importantly, it needs to be ensured that AI is working in a private, secure, and ethical manner. To do this, one first needs to understand what exactly is private, secure, and ethical use of AI in healthcare. This thesis aims to do just that by highlighting various privacy, security, and ethical issues that are prevalent in AI-based healthcare. In this thesis, the AI-based strategies and techniques that have been created to overcome these issues in privacy, security, and ethics, are also briefly discussed. This thesis uses literature from various sources and creates a comprehensive overview of AI in healthcare, keeping privacy, security, and ethical aspects as the main focus.

Svitlana Dorociak. Bachelorarbeitsabschlussvortrag. 07. Februar 2024, 14:00 Uhr, F2.419

Zahlreiche relevante Systeme der realen Welt lassen sich als Netzwerke bzw. Graphen abbilden und ermöglichen umfassende Analysen. Beispiele dafür umfassen soziale Netzwerke (z. B. Freundschafts- und Beziehungsnetzwerke), technologische Netzwerke (z. B. Energieversorgungsnetze), biologische Netzwerke (z. B. Protein-Protein-Interaktionsnetzwerke), interorganisationale Netzwerke (z. B. Netzwerke von Geschäftsbeziehungen) sowie Informationsnetzwerke (z. B. Zitationsnetzwerke).
Durch die Analyse der in realen Netzwerken häufig vorkommenden Verbindungsmuster wird ein besseres Verständnis für Netzwerkstrukturen höherer Ordnung ermöglicht. In diesem Zusammenhang gewinnen diese sogenannten Netzwerkmotive in verschiedenen Anwendungsgebieten zunehmend an Bedeutung. Eine Herausforderung besteht darin, dass Analysen komplexer Netzwerke erheblichen Rechen- und Speicheraufwand erfordern. Einen Lösungsansatz stellen Methoden zur Sparsifizierung der Graphen dar, wobei relevante Eigenschaften des ursprünglichen Graphen dabei möglichst erhalten bleiben sollten.
Im Rahmen der vorliegenden Arbeit wurde ein Algorithmus zur motivbasierten Schnitt-Sparsifizierung implementiert. Der implementierte Algorithmus wurde mit verschiedenen Werten der Parameter auf verschiedene Eingabegraphen angewendet, um seine Leistung in verschiedenen Szenarien zu überprüfen. Aus den durchgeführten Tests konnten Erkenntnisse zur Auswahl der Parameterwerte sowie der Wahrscheinlichkeit für die Kantenwahl gewonnen werden.

Jonas Harbig. 31. Januar 2024, 14:00 Uhr, F2.419

We consider the problem of forming an arbitrary connected pattern $P$ with $n$ robots in the \oblot model.
In this model, the (deterministic) robots are indistinguishable, have no common orientation, and cannot store past observations nor communicate with each other.
The robots receive $P \subseteq \R^{^2}$ as a finite subset of coordinates and the goal is to place one robot at each coordinate.
Previous work considered this problem under global visibility~\cite{DBLP:journals/tcs/YamashitaS10} and limited visibility but with memory~\cite{DBLP:conf/sirocco/YamauchiY13} (robots can store past observations).
In both cases it was shown that $P$ can be formed if the robots' initial placement is not too symmetric compared to $P$.

Without memory and with limited visibility, forming such patterns remains an open problem.
We solve this setting partially by showing that any connected pattern can be formed if the robots see each other in the (not too symmetric) initial placement.
For this, we partition $P$ into suitable components that are rotation-symmetric to each other and exploit the robots' initial mutual visibility to form one cluster per component.
Using a careful placement of the clusters and their robots, we show that each cluster can move in a coordinated way through its component, dropping one robot per pattern coordinate along the way, yielding the desired pattern.

Jan-Luca Hansel. 24. Januar 2024, 14:00 Uhr, F2.419

Conversational agents, i.e., systems which try to emulate human dialogue, allow users to interact with automated services in a more natural way. When they appear in a virtual world in the guise of a normal user, they can increase the feeling of immersion in this virtual world. Now, to be able to conduct a multi-turn conversation with a human, a conversational agent needs a dialogue strategy. In this talk, a technique is presented which is able to enhance an initial dialogue strategy by the means of statistical methods. Furthermore, a framework for conversational agents is presented which demonstrates how a dialogue strategy is employed to build a conversational agent.

Shariq Majeed. Masterarbeitsabschlussvortrag. 17. Januar 2024, 14:00 Uhr, F2.419

This study investigates the strengths and weaknesses of classical occlusion culling algorithms on modern hardware. It focuses on how occlusion culling affects the efficiency and effectiveness of the algorithms. It also tries to dertermine the impact of occlusion queries on the final image. It compares five redenering algorithms that employ different occlusion culling strategies. Tehe algorithms elected in this study were implemented in PADrend using C++ and EScript. This study tests each algorithm, the studycompares these algorithms. The result reveals that the frame duration is not directly proportional to the occlusion queeries. However, the complexity of the scene directly affects the frame duration. The study concludes that no algorithm is significantly superior to the other.

André Graute. 10. Januar 2024, 14:00 Uhr, F2.419

Neural Rendering using Neural Radiance Fields (NeRF) is a technique that uses deep learning algorithms to create photorealistic images and videos. It is widely used in computer graphics and animation to create more realistic and lifelike images. One of the main challenges in rendering NeRF are the high computational costs, which can make it difficult to achieve real-time performance. For real-time applications, it is therefore crucial to speed up the rendering process and make it more efficient without suffering any loss of quality. Common techniques for accelerating rendering are the use of spatial data structures or approximation algorithms. In this talk, a technique will be presented that uses point clouds to both speed up rendering and improve quality.

Jinfeng Dou. 20. Dezember 2023, 14:00 Uhr, F2.419

We introduce the Cloud Assisted Blockchain (CAB) model, a novel approach to distributed computing that leverages the inherent characteristics of cloud environments. The primary focus is developing a scalable state machine replication (SMR) solution within a federated cloud model. The CAB model integrates various techniques, including hashing, median rule, Merkel hash tree, and the arrow protocol, to achieve consensus with less time(round) and work(message communication and transaction memories). The comprehensive model presented in this paper provides insights into the intricate balance between decentralization, reliability, and practical considerations in distributed computing scenarios.

Prof. Dr. Martin Gairing, University of Liverpool, UK. 15. Joint work with Miriam Fischer and Dario Paccagnan. Dezember 2023, 17:00 Uhr, F0.530

In this work we study the power and limitations of fair interventions in weighted congestion games.  Specifically, we focus on interventions that aim at improving the equilibrium quality (price of anarchy) and are fair in the sense that identical players receive identical treatment. Within this setting, we provide three key contributions: First, we show that no fair intervention can reduce the price of anarchy below a given factor depending solely on the class of latencies considered. Interestingly, this lower bound is unconditional, i.e., it applies regardless of how much computation interventions are allowed to use. Second, we propose a taxation mechanism that is fair and show that the resulting price of anarchy matches this lower bound, while the mechanism can be efficiently computed in polynomial time. Third, we complement these results by showing that no intervention (fair or not) can achieve a better approximation if polynomial computability is required. We do so by proving that the minimum social cost is NP-hard to approximate below a factor identical to the one previously introduced. In doing so, we also show that the randomized algorithm proposed by Makarychev and Sviridenko [JACM’2018] for the class of optimization problems with a “diseconomy of scale” is optimal, and provide a novel way to derandomize its solution via equilibrium computation.

Vortragender: Björn Beckendorf. Masterarbeitsabschlussvortrag. 06. Dezember 2023, 14:00 Uhr, F2.419

In this thesis, we tackle the challenge of creating and maintaining graph structures that support efficient routing in overlay networks with a distributed, self-stabilizing algorithm. There exist different algorithms for several graph structures, that mostly use identifiers to build the networks. The (B,c)-Skip-Graph is based on the well-established Skip-Graph and takes a metric and two integers B and c as parameters. The distance between two nodes in a (B,c)-Skip-Graph is at most stretched by a factor 1 + ε. As far as we know, there is no self-stabilizing algorithm for a metric graph with such a stretch. In this thesis, we extend the (B,c)-Skip-Graph to the (B,c)-Skip+Graph with some additional edges to allow the construction of a self-stabilizing algorithm for it. Our algorithm builds the graph in poly-logarithmic time from an arbitrary weekly connected graph.

Julian Werthmann. 22. November 2023, 14:00 Uhr, F2.419

We consider a new model of distiributed computation where a powerful computational entity (the cloud) is assisted by several potentially malicious weaker entities (the peers). The main focus on this talk is the presentation and analysis of a distributed mergesort algorithm for this setting.

Additionally, we will briefly discuss other problems and connections to already established models.

18. April 2023, 14:00 Uhr, F2.211
Vortragender: Vineet Vasishta Eranki
Titel: Blockchain CAP Algorithm
Masterarbeitsvortrag
Abstract

25. April 2023, 14:00 Uhr, F2.211
Vortragender: Jonas Schweichhart
Titel: Minimum Edge Cuts in Overlay Networks
Masterarbeitsvortrag
Abstract

15. Mai 2023, 13:00 Uhr, F2.419
Vortragender: Fabian Schneider
Titel: Utilizing Redundancy in Distributed Heterogeneous Storage
Bachelorarbeitsvortrag
Abstract

17. Mai 2023, 14:00 Uhr, F2.419
Vortragender: Jens Schmidt
Titel: Matching Algorithmen in verteilten Systemen
Bachelorarbeitsvortrag
Abstract

25. Mai 2023, 14:00 Uhr, F2.419
Vortragender: Amruta Ranade
Titel: Graph Neural Network based Anomaly Detection in Smart-Grid Electricity Consumption
Masterarbeitsvortrag
Abstract

13. Juni 2023, 14:00 Uhr, F2.419
Vortragende: Osama Ali
Titel: Highly accurate deep compressed facial recognition
Mastarbeitsvortrag
Abstract

14. Juni 2023, 14:00 Uhr, F2.419
Vortragende: Jinfeng Dou
Titel: Using Path Separators in Planar graphs and minor free Graphs
Abstract

20. Juni 2023, 14:00 Uhr, F2.419
Vortragender: Nivedita Ashri
Titel: Virtual On-Demand Volunteer System Based on Delaunay Triangulation
Masterarbeitsvortrag
Abstract

21. Juni 2023, 14:00 Uhr, F2.419
Vortragender: Julian Werthmann
Titel: Routing Schemes for Hybrid Communication Networks
Abstract

28. Juni 2023, 14:00 Uhr, F2.419
Vortragender: Thorsten Götte
Titel: Compact Routing in Planar Graphs: An Overview and an Outlook.
Abstract

07. Juli 2023, 14:00 Uhr, F2.419
Vortragende: Tumkur Nagaraj Gowda Sushmitha
Titel: Improving the End-of-Line Test of Custom-Built Geared Motors using Clustering based on Neural Networks
Mastarbeitsvortrag
Abstract

19. Juli 2023, 14:00 Uhr, F2.419
Vortragender: Andreas Padalkin
Titel: Collision Detection for Modular Robots -- it is easy to cause collisions and hard to avoid them
Abstract

16. August 2023, 14:00 Uhr, F2.419
Vortragender: David Liedtke
Titel: Shape Formation by 3D Hybrid Programmable Matter
Abstract

23. August 2023, 14:00 Uhr, F2.419
Vortragender: Leo Decking
Titel: Zuweisung verteilter Speicher unter Maximierung der minimalen gewichteten Bandbreite
Bachelorarbeitsvortrag
Abstract

13. September 2023, 14:00 Uhr, F2.419
Vortragender: Volker Deppe
Titel: Routing in Hypergraphs
Bachelorarbeitsvortrag
Abstract

27. September 2023, 14:00 Uhr, F2.419
Vortragender: Jonas Friemel
Titel: Shape Reconfiguration by Hybrid Programmable Matter
Masterarbeitsvortrag
Abstract

27. September 2023, 15:00 Uhr, F2.419
Vortragender: Vipasyan Telaprolu
Titel: Reconstruction of 3D Surfels from Neural Radiance Fields
Masterarbeitsvortrag
Abstract

27. September 2023, 16:00 Uhr, F2.419
Vortragender: Alexander Nickel
Titel: Entwicklung und Analyse von Formeln zur Abschätzung der Renderingzeit eines Frames
Bachelorarbeitsvortrag
Abstract

22. November 2022, 14:00 Uhr, Zoom + F2.211
Vortragender: Julian Werthmann
Titel: The Minor Aggregation Model
Abstract

29. November 2022, 14:00 Uhr, Zoom
Vortragender: Sneha Hiremath
Titel: Design and Implementation of an ML-Based Data Cleaning Method for Structured Data
Masterarbeitsvortrag
Abstract

6. Dezember 2022, 14:00 Uhr, Zoom
Vortragende: Jinfeng Dou
Titel: The Sparse Cover in Compact Routing
Abstract

16. Dezember 2022   Fachgruppen-Kolloquium  Raum F0.231

14:00 Uhr – 14:45 Uhr
Vortragender: Prof. Dr. John Augustine, IIT Madras, Indien
Titel: Three Vignettes from the Distributed Trust Paradigm of Computing
Abstract

14:45 Uhr – 15:30 Uhr
Vortragender: Prof. Dr. Ran Gelles, Bar-Ilan University, Israel
Titel: Distributed Computations in Fully-Defective Networks
Abstract

15:30 Uhr - 16:00 Uhr Kaffeepause

16:00 Uhr – 16:45 Uhr
Vortragender: Prof. Dr. Martin Gairing, University of Liverpool, UK
Titel: In Congestion Games, Taxes Achieve Optimal Approximation
Abstract

16:45 Uhr – 17:30 Uhr
Vortragender: Prof. Dr. Ulf Lorenz, Universität Siegen
Titel: A model&run approach for multistage robust optimization
Abstract

31. Januar 2023, 14:00 Uhr, Zoom + F1.310
Vortragender: Thorsten Götte
Titel: More (Almost) Optimal Compact Routing Schemes
Abstract

21. Februar 2023, 14:00 Uhr, F2.211
Vortragender: David Liedtke
Titel: A Universal Coating Algorithm for 3D Hybrid Programmable Matter
Abstract

14. März 2023, 14:00 Uhr, Zoom
Vortragender: Andreas Padalkin
Titel: Joint Movement Extension to the Geometric Amoebot Model
Abstract

21. März 2023, 13:00 Uhr, Zoom + F2.211
Vortragender: Daniel Warner
Titel: Deterministic Leader Election in the 3D Amoebot Model
Abstract

3. Mai 2022, 14:00 Uhr, F2.211 + Zoom
Vortragender: Julian Werthmann
Titel: Distributed Algorithms for Hybrid Radio Networks
Abstract
(PhD Startertalk)

24. Mai 2022, 14:00 Uhr, Zoom
Vortragender: Andreas Padalkin
Titel: Reconfigurable Circuits and Joint Movements in the Geometric Amoebot Model
Abstract
(PhD Startertalk)

25. Mai 2022, 14:00 Uhr, F1.110
Vortragender: Henning Hillebrandt
Titel: Verteiltes Berechnen kompakter Routingtabellen in Unit Disk Graphen
Abstract
Bachelorarbeitsvortrag

21. Juni 2022, 14:00 Uhr, Zoom
Vortragende: Jinfeng Dou
Titel: PIM meets Cloud-Assisted Peer-to-Peer Systems
Abstract

5. Juli 2022, 14:30 Uhr, Zoom
Vortragender: David Liedtke
Titel: Universal Coating in the 3D Hybrid Model by a Single Finite Automaton Robot
Abstract
(PhD Startertalk)

23. August 2022, 13:45 Uhr, Zoom
Vortragender: Daniel Warner
Titel: Fault-Tolerant Algorithms in the Amoebot Model
(PhD Startertalk)
Abstract

30. August 2022, 14:00 Uhr, Zoom
Vortragender: Thorsten Götte
Titel: (Almost) Optimal Compact Routing Schemes using Padded Decompositions
Abstract

6. September 2022, 14:00 Uhr, F1.310 + Zoom
Vortragender: Chrstian Scheideler
Titel: Critical path analysis and its applications
Abstract

13. September 2022, 14:00 Uhr, F1.310 + Zoom
Vortragender: Ran Gelles, Bar-Ilan University
Titel: Distributed computation with limited communication
Abstract

2. November 2021, 14:00 Uhr, F2.211
Vortragender: Vaibhav Adsul
Titel: Peer-to-Peer Matching for Distributed Systems
(Masterarbeitsvortrag)
Abstract

9. November 2021, 14:00 Uhr, F2.211
Vortragender: Dennis Suermann
Titel: Schutz und Stabilisierung von Overlay-Netzwerken mithilfe des Relay-Layers
Implementierung und Erweiterung des Relay-Modells in Bezug auf der Denial of Service Resistenz mit anschließender Praxisanalyse des Finite Departure Problems
(Bachelorarbeitsvortrag)
Abstract

7. Dezember 2021, 14:00 Uhr, via Zoom
Vortragender: Prof. Dr. Christian Scheideler
Titel: Cloud-Assisted Peer-to-Peer Systems
Abstract

14. Dezember 2021, 14:00 Uhr, via Zoom
Vortragender: Sebastian Siegfried Korzeczek
Titel: Aufarbeitung und Implementierung von DAG-Rider
(Bachelorarbeitsvortrag)
Abstract

11. Januar 2022, 14:00 Uhr, via Zoom
Vortragender: David Liedtke
Titel: Universal Coating in 3D Hybrid Model by a Single Finite Automaton 
Abstract

12. Januar 2022, 14:00 Uhr, via Zoom
Vortragender: Simon Guntermann
Titel: Untersuchung von Symmetrieeigenschaften mit einem endlichen-Automaten-Roboter
(Bachelorarbeitsvortrag)
Abstract

18. Januar 2022, 14:00 Uhr, via Zoom
Vortragender: Marcel Nachtigall
Titel: Hybrid Routing in Three Dimensions
(Masterarbeitsvortrag)
Abstract

1. Februar 2022, 14:00 Uhr, via Zoom
Vortragender: Andreas Padalkin
Titel: Consensus Problems in the Reconfigurable Circuit Model
Abstract

8. Februar 2022, 14:00 Uhr, via Zoom
Vortragender: Thorsten Götte
Titel: The Power of Multiple Identies: Asynchronous Byzantine Reliable Broadcast with Improved Resilience through Collusion
Abstract

22. Februar 2022, 14:00 Uhr, via Zoom
Vortragende: Rajanna Rooopa
Titel: Evaluation of Algorithms for the Node Capacitated Clique
(Masterarbeitsvortrag)
Abstract

8. März 2022, 14:00 Uhr, via Zoom
Vortragender: Julian Werthmann
Titel: Hybrid Routing in UDGs with many holes
Abstract

22. März 2022, 14:00 Uhr, via Zoom
Vortragender: Daniel Warner
Titel: Symmetry Problems in the Reconfigurable Circuit Model
Abstract

6. April 2021, 14:00 Uhr
Vortragender: Jan David Liedtke
Titel: Exploration and Convex Hull Construction in the Three-Dimensional Hybrid Model
(Masterarbeitsvorarbeitsvortrag)
Abstract
Der Vortrag wird per Zoom übertragen

8. Juni 2021, 14:00 Uhr
Vortragender: Julian Werthmann
Titel: Hybrid Routing in UDGs with a single hole
Abstract
Der Vortrag wird per Zoom übertragen

15. Juni 2021, 14:00 Uhr
Vortragender: Daniel Warner
Titel: tba

22. Juni 2021, 14:00 Uhr
Vortragender: Andreas Padalkin
Titel: Reconfigurable Circuit Model
Abstract
Der Vortrag wird per Zoom übertragen

13. Juli 2021, 14:00 Uhr
Vortragender: Christian Scheideler
Titel: Algorithms for Dynamic Automata Networks
Abstract
Der Vortrag wird per Zoom übertragen

27. Juli 2021, 14:00 Uhr
Vortragender: Thorsten Götte
Titel: Fast Overlay Construction and its Applications
Abstract

14. September 2021, 14:00 Uhr
Vortragender: Leon Everling
Titel: Selbststabilisierender Bakery Algorithmus für verteilte Systeme
(Bachelorarbeitsvortrag)
Abstract
Der Vortrag wird per Zoom übertragen

21. September 2021, 14:00 Uhr
Vortragender: Daniel Warner
Titel: Fault-Tolerant Leader Election in the Amoebot Model
Abstract

9. Oktober 2020, 10:00 Uhr, F1.110
Vortragender: Moritz Jochmaring
Titel: A self stabilizing protocol for well-formed trees in hybrid networks
(Masterarbeitsvorarbeitsvortrag)
Abstract

1. Dezember 2020, 14:00 Uhr, F1.110
Vortragender: Julian Werthmann
Titel: Derandomization and Local Graph Problems in the Node-Capacitated Clique
(Masterarbeitsvortrag)
Abstract

8. Dezember 2020, 14:00 Uhr, F1.110
Vortragender: Mengshi Ma
Titel: Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter
(Bachelorarbeitsvortrag)
Abstract

15. Dezember 2020, 14:00 Uhr, F1.110
Vortragender: Thorsten Götte
Titel: Covering Problems in Hybrid Communication Networks
Abstract

12. Januar 2021, 14:00 Uhr
Vortragender: Christian Scheideler
Titel: Transaction Processing in Distributed Systems
Abstract
Der Vortrag wird per Zoom übertragen

02. Februar 2021, 14:00 Uhr
Vortragender: Kristian Hinnenthal
Titel: Fast Overlay Construction in Hybrid Networks
Abstract
Der Vortrag wird per Zoom übertragen

23. Februar 2021, 14:00 Uhr
Vortragender: Michael Feldmann
Titel: Near-Shortest Path Routing in Hybrid Communication Networks
Abstract
Der Vortrag wird per BigBlueButton übertragen

9. März 2021, 14:00 Uhr
Vortragender: Daniel Warner
Titel: Fault Tolerant Hexagon Shape Formation in the Amoebot Model
Der Vortrag wird per BigBlueButton übertragen
Abstract

6. April 2021, 14:00 Uhr, F1.110
Vortragender: David Liedtke
Titel: tba
(Masterarbeitsvortrag)

14. April 2020, 10:00 Uhr, Medium: Skype
Vortragender: Andreas Guggenmos
Titel: Algorithmen für selbststabilisierende Skip+-Delaunaygraphen
(Bachelorarbeitsvortrag)
Abstract

26. Mai 2020, 14:00 Uhr
Vortragender: Christian Scheideler
Titel: Asynchrony and Concurrency Control in the Amoebot Model
Abstract
Der Vortrag wird als Video Konferenz übertragen:
https://uni-paderborn.webex.com/meet/scheideler

23. Juni 2020, 14:00 Uhr
Vortragender: Thorsten Götte
Titel: Time-Optimal Construction of Overlays
Abstract
Der Vortrag wird als Video Konferenz übertragen:
https://zoom.us/j/99267152953

07. Juli 2020, 14:15 Uhr
Vortragender: Daniel Warner
Titel: First steps towards fault-tolerant shape formation in the amoebot model
Abstract
Der Vortrag wird als Video Konferenz übertragen:
https://zoom.us/j/9791497445

21. Juli 2020, 14:00 Uhr
Vortragender: Kristian Hinnenthal
Titel: Single-Source Shortest Paths in Hybrid Networks
Abstract
Der Vortrag wird als Video Konferenz übertragen:
https://zoom.us/j/9791497445

24. August 2020, 10:00 Uhr
Vortragender: Paresh Yeole
Titel: Plurality Consensus in Hybrid Vehicular Networks
(Masterarbeitsvorarbeitsvortrag)
Abstract
Der Vortrag wird per BigBlueButton übertragen:
https://bbb.uni-paderborn.de/b/chr-z74-dwr
Zugangscode: 146150

17. Dezember 2019, 14:00 Uhr, Raum F2.211
Vortragender: Thorsten Götte
Titel: Conductance Testing in the Node Capacitated Clique
Abstract

20. Dezember 2019, 16:00 Uhr, Raum F0.530
Vortragender: Prof. Dr. Henning Meyerhenke (HU Berlin)
Titel: Fast Group Centrality Algorithms for Large Graphs
Abstract

20. Dezember 2019, 16:45 Uhr, Raum F0.530
Vortragender: Prof. Dr. Stefan Schmid (Universität Wien)
Titel: Demand-Aware Graphs and Self-Adjusting Network
Abstract

7. Januar 2020, 14:00 Uhr, Raum F2.211
Vortragender: Daniel Warner
Titel: On the complexity of local transformations in SDN overlays
(Masterarbeitsvortrag)
Abstract

25. Februar 2020, 14:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Time- and Space-Optimal Clock Synchronization in the Beeping Model
Abstract

23. März 2020, 11:00 Uhr, via Skype
Vortragender: Michael Skowronek
Titel: Approaches for Competitive Routing through Intersections of Hole Abstractions in Hybrid Communication Networks
(Bachelorarbeitsvortrag)
Abstract

31. März 2020, 14:00 Uhr, via Zoom (zoom.us/j/9791497445)
Vortragender: Kristian Hinnenthal
Titel: Fast Hybrid Network Algorithms for Shortest Paths in Sparse Graphs
Abstract

16. April 2019, 13:15 Uhr, Raum F2.211
Vortragende: Christina Kolb
Titel: On Gossip in Hybrid Networks
Abstract

7. Mai 2019, 14:00 Uhr, Raum F2.211
Vortragender: Christian Scheideler
Titel: Distributed algorithms for hybrid networks
Abstract

4. Juni 2019, 14:00 Uhr, Raum F2.211
Vortragender: Kristian Hinnenthal
Titel: Distributed Computation in Node-Capacitated Networks
Abstract

11. Juni 2019, 13:15 Uhr, Raum F2.211
Vortragender: Naveen Kumar Kotta Halappa
Titel: Implementation and Evaluation of Authenticated Data Structures Using Intel SGX Enclaves
Abstract
(Masterarbeitsvortrag)

18. Juni 2019, 14:00 Uhr, Raum F2.211
Vortragender: Thorsten Götte
Titel: Faster Construction of Overlay Networks
Abstract

2. Juli 2019, 14:00 Uhr, Raum F2.211
Vortragender: Alexander Setzer
Titel: On the Complexity of Local Graph Transformations
Abstract

23. Juli 2019, 14:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Self-stabilizing Congestion Control with Logarithmic Memory
Abstract

24. September 2019, 14:00 Uhr, Raum F2.211
Vortragender: Christian Korfmacher
Titel: Scalable Multi Objective Path Optimization for Multi-Laser Selective Laser Melting Scanning Systems
(Masterarbeitsvortrag)
Abstract

30. Oktober 2018, 14:00 Uhr, Raum F2.211
Vortragender: Alexander Setzer
Titel: A New Approach for the Finite Departure Problem in Overlay Networks
Abstract

20. November 2018, 14:00 Uhr, Raum F2.211
Vortragender: Prof. Dr. Fabian Kuhn, Universität Freiburg
Titel: On the Role of Randomization in Local Distributed Algorithms
Abstract

27. November 2018, 14:00 Uhr, Raum F2.211
Vortragender: Robin Wulfes
Titel: Load-Balanced-Routing in Hybriden Kommunikationsnetzwerken
Abstract
(Bachelorarbeitsvortrag)

4. Dezember 2018, 14:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Skeap & Seap: Scalable Distributed Priority Queues for constant and arbitrary Priorities
Abstract

12. März 2019, 14:00 Uhr, Raum F1.310
Vortragender: Kristian Hinnenthal
Titel: Shape Recognition by a Finite Automaton Robot
Abstract

2. April 2019, 14:00 Uhr, Raum F2.211
Vortragender: Thorsten Götte
Title: Always be Two Steps Ahead of Your Enemy
Abstract

8. Mai 2018, 14:00 Uhr, Raum F2.211
Vortragender: Christian Scheideler
Titel: Monotonic Searchability in Self-Stabilizing Overlays
Abstract

15. Mai 2018, 14:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Skueue: A Scalable and Sequentially Consistent Distributed Queue
Abstract

28. Juni 2018, 14:30 Uhr, Raum F2.211
Vortragende: Jan Bobolz + Alexander Setzer
Titel: Provably Anonymous Communication Based on Trusted Execution Environments
Abstract

3. Juli 2018, 14:00 Uhr, Raum F2.211
Vortragender: Thorsten Götte
Titel: Random Walks in Dynamic Networks
Abstract

11. September 2018, 14:00 Uhr, Raum F2.211
Vortragende: Christina Kolb + Jannik Sundermeier
Titel: Reducing the Number of Cellular Infrastructure Nodes for Routing in Hybrid Communi- cation Networks with Holes
Abstract

20. September 2018, 14:00 Uhr, Raum F1.310
Vortragender: Dorian Rudolph (Bachelor-Abschlussvortrag)
Titel: Decontaminating Planar Regions With Finite Automaton Robots And Tiles
Abstract

24. Oktober 2017, 14:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Searching for other participants is one of the most important operations in a distributed system
Abstract

24. Oktober 2017, 14:45 Uhr, Raum F2.211
Vortragender: Jannik Sundermeier
Titel: Routing in Hybrid Communication Networks with Holes - Considering Bounding Boxes as Hole Abstractions (Masterarbeitsvortrag)
Abstract

25. Oktober 2017, 14:00 Uhr, Raum F2.211
Vortragender: Thorsten Götte
Titel: Self-Stabilizing Spanners for Tree Metrics (Masterarbeitsvortrag)
Abstract

7. November 2017, 14:00 Uhr, Raum F2.211
Vortragender: Thim Frederik Strothmann
Titel: Improved Leader Election for Self-Organizing Programmable Matter
Abstract

14. November 2017, 14:00 Uhr, Raum F2.211
Vortragender: Andreas Schenk
Titel: Monotone Suchbarkeit in mehrdimensionalen verteilten Datenstrukturen (Bachelorarbeitsvortrag)
Abstract

28. November 2017, 14:00 Uhr, Raum F2.211
Vortragender: Alexander Setzer
Titel: Just-In-Time-Teaching in Informatik-Übungen - ein Lehrforschungsprojekt
Abstract

5. Dezember 2017, 14:00 Uhr, Raum F2.211
Vortragender: Björn Beckendorf
Titel: Visualisierung zu Algorithmen verteilter Netzwerksysteme (Bachelorarbeitsvortrag)
Abstract

19. Dezember 2017, 14:00 Uhr, Raum F2.211
Vortragender: Kristian Hinnenthal
Titel: Towards a More General Overlay Network Model: The Node-Congested Clique
Abstract

13. März 2018, 14:00 Uhr, Raum F2.211
Vortragende: Christina Kolb
Titel: Competitive Routing in Hybrid Communication Networks
Abstract

19. März 2018, 11:15 Uhr, Raum F2.419
Vortragende: Moritz Jochmaring
Titel: Monotone Suchbarkeit bei den selbststabilisierenden Protokollen Build-List und Build-Multilist mit systemverlassenden Knoten
Abstract

21. April 2017, 14:00 Uhr, Raum F2.211
Vortragende: Ngoc Chi Banh
Titel: An Asynchronous Adaptation of a Churn-resistant Overlay Network (Bachelorarbeitsvortrag)
Abstract

28. April 2017, 14:00 Uhr, Raum F2.211
Vortragende: Christian Scheideler
Titel: Algorithmen für ein Trusted Communication Modell, Teil II
Abstract

2. Mai 2017, 14:00 Uhr, Raum F1.110
Vortragende: Linghui Luo
Titel: MultiSkipList: A Self-stabilizing Overlay Network with Monotonic Searchability maintained (Masterarbeitsvortrag)
Abstract

19. Mai 2017, 14:00 Uhr, Raum F2.211
Vortragender: Alexander Setzer
Titel: Towards a new model for trusted computing
Abstract

22. September 2017, 14:00 Uhr, Raum F2.211
Vortragender: Till Knollmann
Titel: A self-stabilizing Protocol for Graphs of Diameter Two
(Masterarbeitsvortrag)
Abstract

25. November 2016, 13:00 Uhr, Raum F2.211
Vortragender: Christian Scheideler
Titel: Algorithmen für ein Trusted Communication Model (Abstract)

9. Dezember 2016, 13:00 Uhr, Raum F2.211
Vortragender: Thim Frederik Strothmann
Titel: Universal Shape Formation for Programmable Matter (Abstract)

27. Januar 2017, 13:00 Uhr, Raum F2.211
Vortragender: Michael Feldmann
Titel: Self-Stabilizing Publish/Subscribe Systems (Abstract)

24. Februar 2017, 13:00 Uhr, Raum F2.211
Vortragender: Kristian Hinnenthal
Titel: Distributed Monitoring of Network Properties: The Power of Hybrid Networks (Abstract)

3.  März 2017, 13:00 Uhr, Raum F2.211
Vortragender: Christina Kolb
Titel: Routing in Hybrid Communication Networks with Holes  -  based on Delaunay Triangulations (Abstract)

23. März 2017, 13:00 Uhr, Raum F2.211
Vortragender: Robert Gmyr
Titel: Forming Tile Shapes with a Single Robot (Abstract)

31.  März 2017, 13:00 Uhr, Raum F2.211
Vortragender: Michél Burkhardt
Titel: Untersuchungen zum Cone-Hashing (Bachelorarbeitsvortrag)
(Abstract)

26. April 2016, 14:15 Uhr, Raum F1.110
Vortragende: Christina Kolb
Titel: How to route in Graphs with Holes? (Abstract)

7. Juni 2016, 14:15 Uhr, Raum F1.110
Vortragender: Jonas Lefèvre
Titel: Fast Self-Stabilizing Metric Algorithm (Abstract)

14. Juni 2016, 14:15 Uhr, Raum F1.110
Vortragender: Robert Gmyr
Titel: Churn- and DoS-resistant Overlay Networks Based on Network Reconfiguration

21. Juni 2016, 14:15 Uhr, Raum F1.110
Vortragender: Robert Gmyr
Titel: Universal Shape Formation for Programmable Matter

19. Juli 2016, 14:15 Uhr, Raum F1.110
Vortragender: Michael Feldmann
Titel: Self-stabilizing networks with constant diameter (Abstract)

20. September 2016, 14:15 Uhr, Raum F1.110
Vortragender: Alexander Setzer
Titel: Towards a Universal Approach for Monotonic Searchability in Self-Stabilizing Overlay Networks (Abstract)

28. September 2016, 14:15 Uhr, Raum F1.310
Vortragender: Kristian Hinnenthal
Titel: Aggregation in Overlay Networks (Abstract)
(Masterarbeitsvortrag)

4. Oktober 2016, 14:15 Uhr, Raum F1.110
Vortragender: Sebastian Heuchler
Titel: Nibbler: Implementing a Turing machine to simulate the Busy Beaver problem (Abstract)
(Bachelorarbeitsvortrag)