Welcome to the Computer Networks group!

The Computer Networks group conducts research and teaching activities focusing on networked systems of all kinds, ranging from large-scale cloud data centers to tiny low-power IoT devices. The group is headed by Prof. Lin Wang. 

We are looking for multiple postdocs, PhDs, and SHKs to join our group. Please check the vacancies here.

News

  • 04.2024: Paper on accelerated synchronization for battery-free IoT accepted to ACM APNet 2024.
  • 03.2024: Paper on autoscaling of inference serving systems accepted to ACM EuroMLSys@EuroSys 2024.
  • 01.2024: Paper on efficient serverless GNN serving accepted to ACM The Web Conference (WWW) 2024.
  • 12.2023: Two papers accepted to IEEE INFOCOM 2024.
  • 11.2023: RICS received the Best Paper Award at IEEE IPCCC 2023.

Research

We focus our research on networked systems and we strive to create concepts and methods to make networked systems more efficient, scalable, usable, and sustainable. Our focus is on creating better programming tools, middleware, and protocols, leveraging the capabilities offered by emerging hardware. Our research has been generously supported by various funding sources including the German Research Foundation (DFG), the Dutch Research Council (NWO), Google Research, and Intel. 

In-Network Acceleration

The emergence of programmable network devices (P4 switches, SmartNICs, and DPUs) has motivated a new concept called in-network computing. We are exploring how programmable network elements can better contribute to computation acceleration in the post-Moore's law era.

Sustainable IoT

IoT systems are ubiquitous nowadays. Yet, virtually all IoT devices rely on battery to function. Batteries are hazardous, prone to disasters, and hard to maintain --- all indicating that current IoT systems are not sustainable. We are working towards sustainable IoT systems by removing completely the batteries from IoT devices.

Systems for Machine Learning

Machine learning is powering many of our intellegent services in our daily life. Yet, serving computation-intensive machine learning workloads while meeting their stringent throughput/latency requirements remains a critical challenge. We are developing efficient network systems across the cloud and edge to support machine learning inference.

Teaching

Our teaching is focused on networked systems. Our recent, current, and upcoming course offerings are listed below. Note that the upcoming ones are projections based on offerings in last year and may be subject to changes. We offer thesis projects at both bachelor and master levels continuously. Please check this page for currently offered thesis topics.

Module Semester ECTS Language Lecturer
Computer Networks WS24/25 6 English/German Prof. Dr. Lin Wang
L.079.05820: Advanced Networked Systems SS24 6 English Prof. Dr. Lin Wang
L.079.08010: Seminar: In-Network Computing SS24 2 English Prof. Dr. Lin Wang
L.079.07052: Project Group: Networked Systems SS24 12 English Prof. Dr. Lin Wang
L.079.05506: Computer Networks WS23/24 6 English Prof. Dr. Lin Wang

 

 

Team

We are a dynamic, international team with members coming from different countries and with different backgrounds. Please check this page to know more about our group and all members.

Contact

Prof. Dr. Lin Wang

Computer Networks

Room O3.149
Paderborn University
Pohlweg 51
33098 Paderborn

+49 5251 60-5375 Send E-Mail Directions