News and Announcements

• Thomas Kapp and Lorenz Pusch awarded Distinguished Students 2024

  November 28, 2024
  
  We congratulate Thomas Kapp and Lorenz Pusch for receiving this year's Distinguished Student award at TKN! With the award, we recognize their valued work and contributions as Student Teaching Assistant and Student Research Assistant, respectively.
  

• Merry Christmas! TKN Christmas Party!

  November 28, 2024
  
  It's that time of the year again. Christmas is coming and we look back at what happened over the last twelve months. We published many interesting papers, received additional funding, and got to know amazing new team members. This time around, our group celebrated Christmas a bit earlier to make sure Falko Dressler could join in while he was home in Berlin from his sabbatical in Boston. We enjoyed a relaxed celebration and are grateful for our amazing team. Now, we wish all of our friends, collaborators, and followers a wonderful Christmas time, a good (and productive) end to the year 2024 and a Happy New Year!
  

• VDE ITG Ehrenurkunde 2024

  November 27, 2024
  
  Falko Dressler received the VDE ITG Ehrenurkunde 2024 for his support of the German computer networking and communications research community.
  

• Poster Presentation at ACM MobiCom 2024

  November 19, 2024
  
  Our group member Falko Dressler presented our poster Coordinated Group Cycling for Commuting at the 30th ACM International Conference on Mobile Computing and Networking (MobiCom 2024), which was held in Washington, DC. In this paper, we outline how group cycling commutes may be coordinated using communication capabilities of contemporary smartphones. We showcase how group cycling can reduce waiting times and, thus, improve ride comfort and safety in a simulation-based case study.
  

• Keynote at ACM MobiArch 2024

  November 18, 2024
  
  Falko Dressler gave a keynote titled Resilient Edge Computing for 6G Edge-AI at ACM MobiArch 2024, which was held in Washington, DC.
  (link to more information)

• New staff member: Peter Scheepers

  November 13, 2024
  
  We welcome to Peter Scheepers who joined our group in November 2024.
  

• New IEEE Transactions on Nanotechnology article

  November 07, 2024
  
  Our article DNA-Based Nanonetwork for Abnormality Detection and Localization in the Human Body has been accepted for publication in IEEE Transactions on Nanotechnology. This study presents an innovative deoxyribonucleic acid (DNA)-based nanonetwork designed to detect and localize abnormalities within the human body. The concept for the architecture integrates nanosensors, nanocollectors, and a gateway device, facilitating the detection and communication of disease indicators through molecular and intra-body links. Modeling DNA tiles for signal amplification and fusion rules (AND, OR, MAJORITY), the system enhances detection accuracy while enabling real-time localization of health anomalies via machine learning models. Extensive simulations demonstrate the efficacy of this approach in the dynamic environment of human vessels, showing promising detection probabilities and minimal false alarms. This research contributes to precision medicine by offering a scalable and efficient method for early disease detection and localization, paving the way for timely interventions and improved healthcare outcomes.
  (link to more information)

• New IEEE Transactions on Mobile Computing article

  November 01, 2024
  
  Our article Biasing Federated Learning with A New Adversarial Graph Attention Network has been accepted for publication in IEEE Transactions on Mobile Computing. Fairness in Federated Learning (FL) is imperative not only for the ethical utilization of technology but also for ensuring that models provide accurate, equitable, and beneficial outcomes across varied user demographics and equipment. This paper proposes a new adversarial architecture, referred to as Adversarial Graph Attention Network (AGAT), which deliberately instigates fairness attacks with an aim to bias the learning process across the FL. The proposed AGAT is developed to synthesize malicious, biasing model updates, where the minimum of Kullback-Leibler (KL) divergence between the user's model update and the global model is maximized. Due to a limited set of labeled input-output biasing data samples, a surrogate model is created, which presents the behavior of a complex malicious model update. Moreover, a graph autoencoder (GAE) is designed within the AGAT architecture, which is trained together with sub-gradient descent to reconstruct manipulatively the correlations of the model updates, and maximize the reconstruction loss while keeping the malicious, biasing model updates undetectable. The proposed AGAT attack is implemented in PyTorch, showing experimentally that AGAT successfully increases the minimum value of KL divergence of benign model updates by 60.9% and bypasses the detection of existing defense models. The source code of the AGAT attack is released on GitHub.
  (link to more information)

• Paper Presentation at ACM Nanocom 2024

  October 29, 2024
  
  Mobility matters in the nanoscale to implement the connection among nanosensors. Analyzing the terahertz band, Jorge Torres Gómez presented our paper titled Implications of Nanodevice Mobility on Terahertz Communication Links in the Human Vessels at the 11th ACM International Conference on Nanoscale Computing and Communication (NanoCom 2024). We provide a model to evaluate the impact of mobility in the higher layers and implements a realistic model for the displacement, rotation, and power radiation of nanoantennas in the human vessels. The paper aims to guide the design of future protocols in nanonetworks.
  

• Paper Presentation at ACM NanoCom 2024

  October 29, 2024
  
  Delving into simulators for the Internet of Bio-Nano-Things (IoBNT) frameworks, our student member Laurenz Elbner presented the paper BVS-Net: A Networking Tool for Studying THz-based Intra-body Communication Links at the 11th ACM International Conference on Nanoscale Computing and Communication (NanoCom 2024). This research focuses on the communication of in-body nanobots with an out-of-body gateway to evaluate data transmission efficiency, identify potential obstacles, and optimize their design for practical applications. In particular, we introduce BVS-Net, an ns-3 module that models the terahertz communication channel between the nanobots and the external gateway.
  

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