Distributed, Networked & Mobile Systems

Distributed/Mobile systems research at MPI-SWS focuses on the design, implementation, and evaluation of distributed and mobile software systems that are dependable and highly available. Recent research in the group has focused on building systems resistant to arbitrary faults, scalable eventually-consistent services, systems with strong data confidentiality and integrity guarantees, as well as privacy-preserving and secure platforms for mobile social applications.

News

Peter Druschel receives 2025 IEEE TCDP Outstanding Technical Achievement Award

July 2025

Peter Druschel has received the 2025 IEEE TCDP Outstanding Technical Achievement Award for his pioneering contributions to the design and implementation of large-scale distributed systems.

MPI-SWS researchers receive SOSP'24 Distinguished Artifact Award

November 2024

MPI-SWS research group leader Andrea Lattuada and postdoctoral fellow Travis Hance have received the SOSP'24 Distinguished Artifact Award for their paper "Verus: A Practical Foundation for Systems Verification."

MPI-SWS researcher receives OSDI 2024 Best Paper Award

July 2024

Andrea Lattuada and his collaborators have received a Best Paper Award at OSDI 2024 for his paper “Anvil: Verifying Liveness of Cluster Management Controllers.”

Operating Systems course at Saarland University

April 2024

The Summer 2024 Operating Systems course at Saarland University is being co-taught by two MPI-SWS faculty and a faculty member from MPI-INF.

Systems for LLMs Course at Saarland University

October 2023

MPI-SWS faculty are teaching a course on Systems for LLMs at Saarland University in the Winter 2023/2024 semester.

All News

Recent projects

All projects

Papers

Towards Using Llms for Distributed Trace Comparison (Abstract).

Vaastav Anand, Pedro Henrique B. Las-Casas, Rodrigo Fonseca, Antoine Kaufmann.
AIOps 2025.

The Case for Instance-Optimized LLMs in OLAP Databases.

Bardia Mohammadi, Laurent Bindschaedler.
DOLAP 2025.

May the Memory Be With You: Efficient and Infinitely Updatable State for Large Language Models.

Excel Chukwu, Laurent Bindschaedler.
EuroMLSys 2025.

Everything You Wanted to Know About Graph Neural Network Partitioning (But Were Afraid to Ask).

Chongyang Xu, Laurent Bindschaedler.
GRADES/NDA 2025.

Destabilizing Iris.

Simon Spies, Niklas Mück, Haoyi Zeng, Michael Sammler, Andrea Lattuada, Peter Müller, Derek Dreyer.
OOPSLA1 2025.

All papers

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