TY - CONF AB - More and more management and orchestration approaches for (software) networks are based on machine learning paradigms and solutions. These approaches depend not only on their program code to operate properly, but also require enough input data to train their internal models. However, such training data is barely available for the software networking domain and most presented solutions rely on their own, sometimes not even published, data sets. This makes it hard, or even infeasible, to reproduce and compare many of the existing solutions. As a result, it ultimately slows down the adoption of machine learning approaches in softwarised networks. To this end, we introduce the "softwarised network data zoo" (SNDZoo), an open collection of software networking data sets aiming to streamline and ease machine learning research in the software networking domain. We present a general methodology to collect, archive, and publish those data sets for use by other researches and, as an example, eight initial data sets, focusing on the performance of virtualised network functions. AU - Peuster, Manuel AU - Schneider, Stefan Balthasar AU - Karl, Holger ID - 15371 T2 - IEEE/IFIP 15th International Conference on Network and Service Management (CNSM) TI - The Softwarised Network Data Zoo ER - TY - CONF AU - Nuriddinov, Askhat AU - Tavernier, Wouter AU - Colle, Didier AU - Pickavet, Mario AU - Peuster, Manuel AU - Schneider, Stefan Balthasar ID - 15372 T2 - IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) TI - Reproducible Functional Tests for Multi-scale Network Services ER - TY - CONF AB - Offloading packet processing tasks to programmable switches and/or to programmable network interfaces, so called “SmartNICs”, is one of the key concepts to prepare softwarized networks for the high traffic demands of the future. However, implementing network functions that make use of those offload- ing technologies is still challenging and usually requires the availability of specialized hardware. It becomes even harder if heterogeneous services, making use of different offloading and network virtualization technologies, should be developed. In this paper, we introduce FOP4 (Function Offloading Pro- totyping with P4), a novel prototyping platform that allows to prototype heterogeneous software network scenarios, including container-based, P4-switch-based, and SmartNIC-based network functions. The presented work substantially extends our existing Containernet platform with the means to prototype offloading scenarios. Besides presenting the platform’s system design, we evaluate its scalability and show that it can run scenarios with more than 64 P4 switch or SmartNIC nodes on a single laptop. Finally, we presented a case study in which we use the presented platform to prototype an extended in-band network telemetry use case. AU - Moro, Daniele AU - Peuster, Manuel AU - Karl, Holger AU - Capone, Antonio ID - 15373 T2 - IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) TI - FOP4: Function Offloading Prototyping in Heterogeneous and Programmable Network Scenarios ER - TY - CONF AB - Emulation platforms supporting Virtual Network Functions (VNFs) allow developers to rapidly prototype network services. None of the available platforms, however, supports experimenting with programmable data planes to enable VNF offloading. In this demonstration, we show FOP4, a flexible platform that provides support for Docker-based VNFs, and VNF offloading, by means of P4-enabled switches. The platform provides interfaces to program the P4 devices and to deploy network functions. We demonstrate FOP4 with two complex example scenarios, demonstrating how developers can exploit data plane programmability to implement network functions. AU - Moro, Daniele AU - Peuster, Manuel AU - Karl, Holger AU - Capone, Antonio ID - 15374 T2 - IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) TI - Demonstrating FOP4: A Flexible Platform to Prototype NFV Offloading Scenarios ER - TY - CONF AU - Müller, Marcel AU - Behnke, Daniel AU - Bök, Patrick-Benjamin AU - Schneider, Stefan Balthasar AU - Peuster, Manuel AU - Karl, Holger ID - 15375 T2 - IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) TI - Putting NFV into Reality: Physical Smart Manufacturing Testbed ER - TY - CONF AU - Behnke, Daniel AU - Müller, Marcel AU - Bök, Patrick-Benjamin AU - Schneider, Stefan Balthasar AU - Peuster, Manuel AU - Karl, Holger ID - 15376 T2 - IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) TI - NFV-driven intrusion detection for smart manufacturing ER - TY - CONF AU - Berendes, Carsten Ingo ID - 15391 SN - 1865-1348 T2 - Business Information Systems Workshops TI - Towards Analyzing High Street Customer Trajectories - A Data-Driven Case Study ER - TY - JOUR AU - Jochen Baumeister ID - 15416 JF - Quick And Easy Journal Title TI - New Quick And Easy Publication - Will be edited by LibreCat team ER - TY - JOUR AU - An, YW AU - Lobacz, AD AU - Baumeister, Jochen AU - Rose, WC AU - Higginson, JS AU - Rosen, J AU - Swanik, CB ID - 15420 JF - J Athl Train SN - 1062-6050 TI - Negative Emotion and Joint-Stiffness Regulation Strategies After Anterior Cruciate Ligament Injury. ER - TY - JOUR AU - Vogt, Sarah AU - Skjæret-Maroni, N AU - Neuhaus, D AU - Baumeister, Jochen ID - 15421 JF - Int J Med Inform SN - 1386-5056 TI - Virtual reality interventions for balance prevention and rehabilitation after musculoskeletal lower limb impairments in young up to middle-aged adults: A comprehensive review on used technology, balance outcome measures and observed effects. VL - 126 ER -