69 citations · 426 across the 38 of their papers we have counts for
41 papers
FabricCRDT: A Conflict-Free Replicated Datatypes Approach to Permissioned Blockchains
Pezhman Nasirifard, Ruben Mayer, Hans-Arno Jacobsen
With the increased adaption of blockchain technologies, permissioned blockchains such as Hyperledger Fabric provide a robust ecosystem for developing production-grade decentralized…
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training
Nikolai Merkel, Daniel Stoll, Ruben Mayer +1
Recently, graph neural networks (GNNs) have gained much attention as a growing area of deep learning capable of learning on graph-structured data. However, the computational and me…
PrestigeBFT: Revolutionizing View Changes in BFT Consensus Algorithms with Reputation Mechanisms
Gengrui Zhang, Fei Pan, Sofia Tijanic +1
This paper proposes PrestigeBFT, a novel leader-based BFT consensus algorithm that addresses the weaknesses of passive view-change protocols. Passive protocols blindly rotate leade…
How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study
Alexander Erben, Ruben Mayer, Hans-Arno Jacobsen
This paper aims to answer the question: Can deep learning models be cost-efficiently trained on a global market of spot VMs spanning different data centers and cloud providers? To…
Analyzing Geospatial Distribution in Blockchains
Shashank Motepalli, Hans-Arno Jacobsen
Blockchains are decentralized; are they genuinely? We analyze blockchain decentralization's often-overlooked but quantifiable dimension: geospatial distribution of transaction proc…
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey
Jana Vatter, Ruben Mayer, Hans-Arno Jacobsen
Graph Neural Networks (GNNs) are an emerging research field. This specialized Deep Neural Network (DNN) architecture is capable of processing graph structured data and bridges the…