activity
20182026
most citedTowards a Computing Platform for the LEO Edge

43 citations · 222 across the 44 of their papers we have counts for

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Showing 2025Show all

17 papers · 1 filter

cs.DC2025

Analyzing the Impact of Participant Failures in Cross-Silo Federated Learning

Fabian Stricker, David Bermbach, Christian Zirpins

Federated learning (FL) is a new paradigm for training machine learning (ML) models without sharing data. While applying FL in cross-silo scenarios, where organizations collaborate…

cs.DC2025

Investigating the Impact of Isolation on Synchronized Benchmarks

Nils Japke, Furat Hamdan, Diana Baumann +1

Benchmarking in cloud environments suffers from performance variability from multi-tenant resource contention. Duet benchmarking mitigates this by running two workload versions con…

cs.DC2025

DisCEdge: Distributed Context Management for Large Language Models at the Edge

Mohammadreza Malekabbasi, Minghe Wang, David Bermbach

Deploying Large Language Model (LLM) services at the edge benefits latency-sensitive and privacy-aware applications. However, the stateless nature of LLMs makes managing user conte…

cs.DC20252 cited

Towards an Optimized Benchmarking Platform for CI/CD Pipelines

Nils Japke, Sebastian Koch, Helmut Lukasczyk +1

Performance regressions in large-scale software systems can lead to substantial resource inefficiencies, making their early detection critical. Frequent benchmarking is essential f…

cs.DC2025

Towards Energy-Efficient Serverless Computing with Hardware Isolation

Natalie Carl, Tobias Pfandzelter, David Bermbach

Serverless computing provides just-in-time infrastructure provisioning with rapid elasticity and a finely-grained pricing model. As full control of resource allocation is in the ha…

cs.DC2025

Towards a Testbed for Scalable FaaS Platforms

Trever Schirmer, David Bermbach

Most cloud platforms have a Function-as-a-Service (FaaS) offering that enables users to easily write highly scalable applications. To better understand how the platform's architect…