activity
20242026
collaborators

31 papers

cs.DB2026

Towards Serverless Processing of Spatiotemporal Big Data Queries

Diana Baumann, Tim C. Rese, David Bermbach

Spatiotemporal data are being produced in continuously growing volumes by a variety of data sources and a variety of application fields rely on rapid analysis of such data. Existin…

cs.DB2026

Spatial Analysis on Value-Based Quadtrees of Rasterized Vector Data

Diana Baumann, Nils Japke, Tim C. Rese +1

Mobility data science offers insights into the complex interconnections of spatial data of moving objects and their surroundings, often based on a combination of vector and raster…

cs.DC2026

Duet instrumentation: An Agentic Approach to Improving Sensitivity in Cloud Service Benchmarking

Sebastian Koch, Nils Japke, David Bermbach

Continuous cloud service performance benchmarking is essential for detecting performance bugs early before deploying them to production. However, detecting performance regressions…

cs.LG2026

FLAM: Evaluating Model Performance with Aggregatable Measures in Federated Learning

Fabian Stricker, Jose A. Peregrina, David Bermbach +1

Performance evaluation is essential for assessing the quality of machine learning (ML) models and guiding deployment decisions. In federated learning (FL), assessing the performanc…

cs.DB2026

GeoBenchr: An Application-Centric Benchmarking Suite for Spatiotemporal Database Platforms

Tim C. Rese, Nils Japke, Diana Baumann +2

The rapid growth of spatiotemporal data volumes needs to be handled by database systems capable of efficiently managing and querying such data. Existing systems such as PostGIS, Sp…

cs.DC2026

FaaSMoE: A Serverless Framework for Multi-Tenant Mixture-of-Experts Serving

Minghe Wang, Trever Schirmer, Mohammadreza Malekabbasi +1

Mixture-of-Experts (MoE) models offer high capacity with efficient inference cost by activating a small subset of expert models per input. However, deploying MoE models requires al…