16 citations · 42 across the 10 of their papers we have counts for
11 papers
Pattern-level Differential Privacy for High-utility Complex Event Processing
He Gu, Thomas Plagemann, Vera Goebel +2
Current privacy-preserving mechanisms (PPMs) in Complex Event Processing (CEP) systems are unnecessarily restrictive, reducing the utility of data received by data consumers. This…
PDSP-Bench: A Benchmarking System for Parallel and Distributed Stream Processing
Pratyush Agnihotri, Boris Koldehofe, Roman Heinrich +2
The paper introduces PDSP-Bench, a novel benchmarking system designed for a systematic understanding of performance of parallel stream processing in a distributed environment. Such…
A Tale of Two Scales: Reconciling Horizontal and Vertical Scaling for Inference Serving Systems
Kamran Razavi, Mehran Salmani, Max Mühlhäuser +2
Inference serving is of great importance in deploying machine learning models in real-world applications, ensuring efficient processing and quick responses to inference requests. H…
Differential Privacy for Protecting Private Patterns in Data Streams
He Gu, Thomas Plagemann, Maik Benndorf +2
Complex event processing (CEP) is a powerful and increasingly more important tool to analyse data streams for Internet of Things (IoT) applications. These data streams often contai…
TCEP: Transitions in Operator Placement to Adapt to Dynamic Network Environments
Manisha Luthra, Boris Koldehofe, Niels Danger +3
Distributed Complex Event Processing (DCEP) is a commonly used paradigm to detect and act on situational changes of many applications, including the Internet of Things (IoT). DCEP…
INetCEP: In-Network Complex Event Processing for Information-Centric Networking
Manisha Luthra, Boris Koldehofe, Jonas Höchst +4
Emerging network architectures like Information-centric Networking (ICN) offer simplicity in the data plane by addressing named data. Such flexibility opens up the possibility to m…