TY - CONF AB - In comparison to classical control approaches in the field of electrical drives like the field-oriented control (FOC), model predictive control (MPC) approaches are able to provide a higher control performance. This refers to shorter settling times, lower overshoots, and a better decoupling of control variables in case of multi-variable controls. However, this can only be achieved if the used prediction model covers the actual behavior of the plant sufficiently well. In case of model deviations, the performance utilizing MPC remains below its potential. This results in effects like increased current ripple or steady state setpoint deviations. In order to achieve a high control performance, it is therefore necessary to adapt the model to the real plant behavior. When using an online system identification, a less accurate model is sufficient for commissioning of the drive system. In this paper, the combination of a finite-control-set MPC (FCS-MPC) with a system identification is proposed. The method does not require high-frequency signal injection, but uses the measured values already required for the FCS-MPC. An evaluation of the least squares-based identification on a laboratory test bench showed that the model accuracy and thus the control performance could be improved by an online update of the prediction models. AU - Hanke, Soren AU - Peitz, Sebastian AU - Wallscheid, Oliver AU - Böcker, Joachim AU - Dellnitz, Michael ID - 10597 SN - 9781538694145 T2 - 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) TI - Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification ER - TY - JOUR AU - Khan, Gohar Feroz AU - Trier, Matthias ID - 10792 IS - 4 JF - European Journal of Information Systems SN - 0960-085X TI - Assessing the long-term fragmentation of information systems research with a longitudinal multi-network analysis VL - 28 ER - TY - CONF AU - Potthast, Martin AU - Gienapp, Lukas AU - Euchner, Florian AU - Heilenkötter, Nick AU - Weidmann, Nico AU - Wachsmuth, Henning AU - Stein, Benno AU - Hagen, Matthias ID - 11709 T2 - 42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019) TI - Argument Search: Assessing Argument Relevance ER - TY - GEN AU - Wachsmuth, Henning ID - 11713 IS - 3 T2 - Computational Linguistics TI - Book Review: Argumentation Mining VL - 45 ER - TY - CONF AU - Ajjour, Yamen AU - Wachsmuth, Henning AU - Kiesel, Johannes AU - Potthast, Martin AU - Hagen, Matthias AU - Stein, Benno ID - 11714 T2 - Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence TI - Data Acquisition for Argument Search: The args.me Corpus ER - TY - JOUR AB - Advances in electromyographic (EMG) sensor technology and machine learning algorithms have led to an increased research effort into high density EMG-based pattern recognition methods for prosthesis control. With the goal set on an autonomous multi-movement prosthesis capable of performing training and classification of an amputee’s EMG signals, the focus of this paper lies in the acceleration of the embedded signal processing chain. We present two Xilinx Zynq-based architectures for accelerating two inherently different high density EMG-based control algorithms. The first hardware accelerated design achieves speed-ups of up to 4.8 over the software-only solution, allowing for a processing delay lower than the sample period of 1 ms. The second system achieved a speed-up of 5.5 over the software-only version and operates at a still satisfactory low processing delay of up to 15 ms while providing a higher reliability and robustness against electrode shift and noisy channels. AU - Boschmann, Alexander AU - Agne, Andreas AU - Thombansen, Georg AU - Witschen, Linus Matthias AU - Kraus, Florian AU - Platzner, Marco ID - 11950 JF - Journal of Parallel and Distributed Computing KW - High density electromyography KW - FPGA acceleration KW - Medical signal processing KW - Pattern recognition KW - Prosthetics SN - 0743-7315 TI - Zynq-based acceleration of robust high density myoelectric signal processing VL - 123 ER - TY - CHAP AU - Senft, Björn AU - Rittmeier, Florian AU - Fischer, Holger Gerhard AU - Oberthür, Simon ID - 11952 SN - 0302-9743 T2 - Design, User Experience, and Usability. Practice and Case Studies TI - A Value-Centered Approach for Unique and Novel Software Applications ER - TY - JOUR AB - As flexible optical devices that can manipulate the phase and amplitude of light, metasurfaces would clearly benefit from directional optical properties. However, single layer metasurface systems consisting of two-dimensional nanoparticle arrays exhibit only a weak spatial asymmetry perpendicular to the surface and therefore have mostly symmetric transmission features. Here, we present a metasurface design principle for nonreciprocal polarization encryption of holographic images. Our approach is based on a two-layer plasmonic metasurface design that introduces a local asymmetry and generates a bidirectional functionality with full phase and amplitude control of the transmitted light. The encoded hologram is designed to appear in a particular linear cross-polarization channel, while it is disappearing in the reverse propagation direction. Hence, layered metasurface systems can feature asymmetric transmission with full phase and amplitude control and therefore expand the design freedom in nanoscale optical devices toward asymmetric information processing and security features for anticounterfeiting applications. AU - Frese, Daniel AU - Wei, Qunshuo AU - Wang, Yongtian AU - Huang, Lingling AU - Zentgraf, Thomas ID - 11953 IS - 6 JF - Nano Letters SN - 1530-6984 TI - Nonreciprocal Asymmetric Polarization Encryption by Layered Plasmonic Metasurfaces VL - 19 ER - TY - JOUR AU - Li, Tianyou AU - Wei, Qunshuo AU - Reineke, Bernhard AU - Walter, Felicitas AU - Wang, Yongtian AU - Zentgraf, Thomas AU - Huang, Lingling ID - 11955 IS - 15 JF - Optics Express SN - 1094-4087 TI - Reconfigurable metasurface hologram by utilizing addressable dynamic pixels VL - 27 ER - TY - CONF AB - We present an unsupervised training approach for a neural network-based mask estimator in an acoustic beamforming application. The network is trained to maximize a likelihood criterion derived from a spatial mixture model of the observations. It is trained from scratch without requiring any parallel data consisting of degraded input and clean training targets. Thus, training can be carried out on real recordings of noisy speech rather than simulated ones. In contrast to previous work on unsupervised training of neural mask estimators, our approach avoids the need for a possibly pre-trained teacher model entirely. We demonstrate the effectiveness of our approach by speech recognition experiments on two different datasets: one mainly deteriorated by noise (CHiME 4) and one by reverberation (REVERB). The results show that the performance of the proposed system is on par with a supervised system using oracle target masks for training and with a system trained using a model-based teacher. AU - Drude, Lukas AU - Heymann, Jahn AU - Haeb-Umbach, Reinhold ID - 11965 T2 - INTERSPEECH 2019, Graz, Austria TI - Unsupervised training of neural mask-based beamforming ER - TY - CONF AU - Bronner, Fabian AU - Sommer, Christoph ID - 11985 SN - 9781538694282 T2 - 2018 IEEE Vehicular Networking Conference (VNC) TI - Efficient Multi-Channel Simulation of Wireless Communications ER - TY - CHAP AU - Reinold, Peter AU - Meyer, Norbert AU - Buse, Dominik AU - Klingler, Florian AU - Sommer, Christoph AU - Dressler, Falko AU - Eisenbarth, Markus AU - Andert, Jakob ID - 12043 SN - 2198-7432 T2 - Proceedings TI - Verkehrssimulation im Hardware-in-the-Loop-Steuergerätetest ER - TY - CHAP AU - Sommer, Christoph AU - Eckhoff, David AU - Brummer, Alexander AU - Buse, Dominik S. AU - Hagenauer, Florian AU - Joerer, Stefan AU - Segata, Michele ID - 12072 SN - 2522-8595 T2 - Recent Advances in Network Simulation TI - Veins: The Open Source Vehicular Network Simulation Framework ER - TY - CONF AU - Yigitbas, Enes AU - Heindörfer, Joshua AU - Engels, Gregor ID - 12076 T2 - Proceedings of the Mensch und Computer 2019 (MuC ’19) TI - A Context-aware Virtual Reality First Aid Training Application ER - TY - GEN AB - Die Komplexität von Steuersystemen gewinnt in der Debatte um den internationalen Steuerwettbewerb zunehmend an Bedeutung. Im vorliegenden Beitrag erfolgt, basierend auf den Daten, die dem Tax Complexity Index (www.taxcomplexity.org) zugrunde liegen, eine umfassende Gegenüberstellung der Komplexität der Steuersysteme von Deutschland und Öster-reich unter Berücksichtigung der Mittelwerte aller Länder. Die Steuergesetze weisen sowohl in Deutschland als auch in Österreich einen verhältnismäßig hohen Grad an Komplexität auf. Bei den steuerlichen Rahmenbedingungen fällt der Grad an Komplexität in beiden Ländern dagegen niedrig aus, wobei Österreich im Durchschnitt weniger komplex ist als Deutschland. AU - Hoppe, Thomas AU - Rechbauer, Martina AU - Sturm, Susann ID - 12077 TI - Steuerkomplexität im Vergleich zwischen Deutschland und Österreich – Eine Analyse des Status quo ER - TY - CONF AU - Feldkord, Björn AU - Knollmann, Till AU - Malatyali, Manuel AU - Meyer auf der Heide, Friedhelm ID - 12870 T2 - Proceedings of the 17th Workshop on Approximation and Online Algorithms (WAOA) TI - Managing Multiple Mobile Resources ER - TY - CONF AB - We propose a training scheme to train neural network-based source separation algorithms from scratch when parallel clean data is unavailable. In particular, we demonstrate that an unsupervised spatial clustering algorithm is sufficient to guide the training of a deep clustering system. We argue that previous work on deep clustering requires strong supervision and elaborate on why this is a limitation. We demonstrate that (a) the single-channel deep clustering system trained according to the proposed scheme alone is able to achieve a similar performance as the multi-channel teacher in terms of word error rates and (b) initializing the spatial clustering approach with the deep clustering result yields a relative word error rate reduction of 26% over the unsupervised teacher. AU - Drude, Lukas AU - Hasenklever, Daniel AU - Haeb-Umbach, Reinhold ID - 12874 T2 - ICASSP 2019, Brighton, UK TI - Unsupervised Training of a Deep Clustering Model for Multichannel Blind Source Separation ER - TY - CONF AB - Signal dereverberation using the Weighted Prediction Error (WPE) method has been proven to be an effective means to raise the accuracy of far-field speech recognition. First proposed as an iterative algorithm, follow-up works have reformulated it as a recursive least squares algorithm and therefore enabled its use in online applications. For this algorithm, the estimation of the power spectral density (PSD) of the anechoic signal plays an important role and strongly influences its performance. Recently, we showed that using a neural network PSD estimator leads to improved performance for online automatic speech recognition. This, however, comes at a price. To train the network, we require parallel data, i.e., utterances simultaneously available in clean and reverberated form. Here we propose to overcome this limitation by training the network jointly with the acoustic model of the speech recognizer. To be specific, the gradients computed from the cross-entropy loss between the target senone sequence and the acoustic model network output is backpropagated through the complex-valued dereverberation filter estimation to the neural network for PSD estimation. Evaluation on two databases demonstrates improved performance for on-line processing scenarios while imposing fewer requirements on the available training data and thus widening the range of applications. AU - Heymann, Jahn AU - Drude, Lukas AU - Haeb-Umbach, Reinhold AU - Kinoshita, Keisuke AU - Nakatani, Tomohiro ID - 12875 T2 - ICASSP 2019, Brighton, UK TI - Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR ER - TY - CONF AB - In this paper, we present libDirectional, a MATLAB library for directional statistics and directional estimation. It supports a variety of commonly used distributions on the unit circle, such as the von Mises, wrapped normal, and wrapped Cauchy distributions. Furthermore, various distributions on higher-dimensional manifolds such as the unit hypersphere and the hypertorus are available. Based on these distributions, several recursive filtering algorithms in libDirectional allow estimation on these manifolds. The functionality is implemented in a clear, well-documented, and object-oriented structure that is both easy to use and easy to extend. AU - Kurz, Gerhard AU - Gilitschenski, Igor AU - Pfaff, Florian AU - Drude, Lukas AU - Hanebeck, Uwe D. AU - Haeb-Umbach, Reinhold AU - Siegwart, Roland Y. ID - 12876 T2 - Journal of Statistical Software 89(4) TI - Directional Statistics and Filtering Using libDirectional ER - TY - CONF AB - By distributing the computational load over the nodes of a Wireless Acoustic Sensor Network (WASN), the real-time capability of the TRINICON (TRIple-N-Independent component analysis for CONvolutive mixtures) framework for Blind Source Separation (BSS) can be ensured, even if the individual network nodes are not powerful enough to run TRINICON in real-time by themselves. To optimally utilize the limited computing power and data rate in WASNs, the MARVELO (Multicast-Aware Routing for Virtual network Embedding with Loops in Overlays) framework is expanded for use with TRINICON, while a feature-based selection scheme is proposed to exploit the most beneficial parts of the input signal for adapting the demixing system. The simulation results of realistic scenarios show only a minor degradation of the separation performance even in heavily resource-limited situations. AU - Guenther, Michael AU - Afifi, Haitham AU - Brendel, Andreas AU - Karl, Holger AU - Kellermann, Walter ID - 12880 T2 - 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (WASPAA 2019) TI - Sparse Adaptation of Distributed Blind Source Separation in Acoustic Sensor Networks ER - TY - CONF AB - Internet of Things (IoT) applications witness an exceptional evolution of traffic demands, while existing protocols, as seen in wireless sensor networks (WSNs), struggle to cope with these demands. Traditional protocols rely on finding a routing path between sensors generating data and sinks acting as gateway or databases. Meanwhile, the network will suffer from high collisions in case of high data rates. In this context, in-network processing solutions are used to leverage the wireless nodes' computations, by distributing processing tasks on the nodes along the routing path. Although in-network processing solutions are very popular in wired networks (e.g., data centers and wide area networks), there are many challenges to adopt these solutions in wireless networks, due to the interference problem. In this paper, we solve the problem of routing and task distribution jointly using a greedy Virtual Network Embedding (VNE) algorithm, and consider power control as well. Through simulations, we compare the proposed algorithm to optimal solutions and show that it achieves good results in terms of delay. Moreover, we discuss its sub-optimality by driving tight lower bounds and loose upper bounds. We also compare our solution with another wireless VNE solution to show the trade-off between delay and symbol error rate. AU - Afifi, Haitham AU - Karl, Holger ID - 12881 T2 - 2019 12th IFIP Wireless and Mobile Networking Conference (WMNC) (WMNC'19) TI - An Approximate Power Control Algorithm for a Multi-Cast Wireless Virtual Network Embedding ER - TY - CONF AB - One of the major challenges in implementing wireless virtualization is the resource discovery. This is particularly important for the embedding-algorithms that are used to distribute the tasks to nodes. MARVELO is a prototype framework for executing different distributed algorithms on the top of a wireless (802.11) ad-hoc network. The aim of MARVELO is to select the nodes for running the algorithms and to define the routing between the nodes. Hence, it also supports monitoring functionalities to collect information about the available resources and to assist in profiling the algorithms. The objective of this demo is to show how MAVRLEO distributes tasks in an ad-hoc network, based on a feedback from our monitoring tool. Additionally, we explain the work-flow, composition and execution of the framework. AU - Afifi, Haitham AU - Karl, Holger AU - Eikenberg, Sebastian AU - Mueller, Arnold AU - Gansel, Lars AU - Makejkin, Alexander AU - Hannemann, Kai AU - Schellenberg, Rafael ID - 12882 KW - WSN KW - virtualization KW - VNE T2 - 2019 IEEE Wireless Communications and Networking Conference (WCNC) (IEEE WCNC 2019) (Demo) TI - A Rapid Prototyping for Wireless Virtual Network Embedding using MARVELO ER - TY - GEN AU - Haltermann, Jan Frederik ID - 12885 TI - Analyzing Data Usage in Array Programs ER - TY - CONF AU - Yigitbas, Enes AU - Jovanovikj, Ivan AU - Sauer, Stefan AU - Engels, Gregor ID - 12889 T2 - Handling Security, Usability, User Experience and Reliability in User-Centered Development Processes (IFIP WG 13.2 & WG 13.5 International Workshop @ INTERACT2019) TI - A Model-based Framework for Context-aware Augmented Reality Applications ER - TY - JOUR AB - We formulate a generic framework for blind source separation (BSS), which allows integrating data-driven spectro-temporal methods, such as deep clustering and deep attractor networks, with physically motivated probabilistic spatial methods, such as complex angular central Gaussian mixture models. The integrated model exploits the complementary strengths of the two approaches to BSS: the strong modeling power of neural networks, which, however, is based on supervised learning, and the ease of unsupervised learning of the spatial mixture models whose few parameters can be estimated on as little as a single segment of a real mixture of speech. Experiments are carried out on both artificially mixed speech and true recordings of speech mixtures. The experiments verify that the integrated models consistently outperform the individual components. We further extend the models to cope with noisy, reverberant speech and introduce a cross-domain teacher–student training where the mixture model serves as the teacher to provide training targets for the student neural network. AU - Drude, Lukas AU - Haeb-Umbach, Reinhold ID - 12890 JF - IEEE Journal of Selected Topics in Signal Processing TI - Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation ER - TY - CONF AU - Augstein, Mirjam AU - Herder, Eelco AU - Wörndl, Wolfgang AU - Yigitbas, Enes ID - 12894 T2 - 30th ACM Conference on Hypertext and Social Media (HT ’19), September 17–20, 2019, Hof, Germany TI - ABIS 2019 – 23rd International Workshop on Personalization and Recommendation on the Web and Beyond ER - TY - JOUR AU - Hammer, Manfred AU - Ebers, Lena AU - Förstner, Jens ID - 12908 JF - Journal of the Optical Society of America B KW - tet_topic_waveguides SN - 0740-3224 TI - Oblique quasi-lossless excitation of a thin silicon slab waveguide: a guided-wave variant of an anti-reflection coating VL - 36 ER - TY - CONF AU - Razzaghi Kouchaksaraei, Hadi AU - Karl, Holger ID - 12912 T2 - 15th International Conference on Network and Service Management (CNSM) TI - Quantitative Analysis of Dynamically Provisioned Heterogeneous Network Services ER - TY - JOUR AU - Reineke, Bernhard AU - Sain, Basudeb AU - Zhao, Ruizhe AU - Carletti, Luca AU - Liu, Bingyi AU - Huang, Lingling AU - de Angelis, Costantino AU - Zentgraf, Thomas ID - 12917 IS - 9 JF - Nano Letters SN - 1530-6984 TI - Silicon metasurfaces for third harmonic geometric phase manipulation and multiplexed holography VL - 19 ER - TY - JOUR AU - Georgi, Philip AU - Massaro, Marcello AU - Luo, Kai Hong AU - Sain, Basudeb AU - Montaut, Nicola AU - Herrmann, Harald AU - Weiss, Thomas AU - Li, Guixin AU - Silberhorn, Christine AU - Zentgraf, Thomas ID - 12919 JF - Light: Science & Applications SN - 2047-7538 TI - Metasurface interferometry toward quantum sensors VL - 8 ER - TY - JOUR AU - Bräuer, Sebastian AU - Plenter, Florian AU - Klör, Benjamin AU - Monhof, Markus AU - Beverungen, Daniel AU - Becker, Jörg ID - 12929 JF - Business Research SN - 2198-3402 TI - Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles ER - TY - JOUR AU - Köthemann, Ronja AU - Weber, Nils AU - Lindner, Jörg K N AU - Meier, Cedrik ID - 12930 IS - 9 JF - Semiconductor Science and Technology SN - 0268-1242 TI - High-precision determination of silicon nanocrystals: optical spectroscopy versus electron microscopy VL - 34 ER - TY - CONF AU - Ajjour, Yamen AU - Alshomary, Milad AU - Wachsmuth, Henning AU - Stein, Benno ID - 12931 T2 - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing TI - Modeling Frames in Argumentation ER - TY - CONF AU - Götte, Thorsten AU - Hinnenthal, Kristian AU - Scheideler, Christian ID - 12944 T2 - Structural Information and Communication Complexity TI - Faster Construction of Overlay Networks ER - TY - CONF AU - Bäumer, Frederik Simon AU - Buff, Bianca ID - 12946 SN - 9789897583773 T2 - Proceedings of the 8th International Conference on Data Science, Technology and Applications TI - How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness ER - TY - JOUR AB - Modern Boolean satisfiability solvers can emit proofs of unsatisfiability. There is substantial interest in being able to verify such proofs and also in using them for further computations. In this paper, we present an FPGA accelerator for checking resolution proofs, a popular proof format. Our accelerator exploits parallelism at the low level by implementing the basic resolution step in hardware, and at the high level by instantiating a number of parallel modules for proof checking. Since proof checking involves highly irregular memory accesses, we employ Hybrid Memory Cube technology for accelerator memory. The results show that while the accelerator is scalable and achieves speedups for all benchmark proofs, performance improvements are currently limited by the overhead of transitioning the proof into the accelerator memory. AU - Hansmeier, Tim AU - Platzner, Marco AU - Pantho, Md Jubaer Hossain AU - Andrews, David ID - 12967 IS - 11 JF - Journal of Signal Processing Systems SN - 1939-8018 TI - An Accelerator for Resolution Proof Checking based on FPGA and Hybrid Memory Cube Technology VL - 91 ER - TY - THES AU - Heindorf, Stefan ID - 15333 TI - Vandalism Detection in Crowdsourced Knowledge Bases ER - TY - GEN AB - n this paper, I review the empirical literature in the intersection of banks and corporate income taxation that emerged over the last two decades. To structure the included studies, I use a stakeholder approach and outline how corporate income taxation plays into the relation of banks and their four main stakeholders: bank regulators, customers, investors and tax authorities. My contribution to the literature is threefold: First, I contribute by providing, to the best of my knowledge, a first comprehensive review on this topic. Second, I point to areas for future research. Third, I deduce policy implications from the studies under review. In sum, the studies show that taxes distort banks’ pricing decisions, the relative attractiveness of debt and equity financing, the decision to report on or off the balance sheet and banks’ investment allocations. Empirical insights on how tax rules affect banks’ decision-making are helpful for policymakers to tailor suitable and sustainable tax legislation directed at banks. AU - Gawehn, Vanessa ID - 15367 KW - corporate income taxes KW - banks KW - stakeholder approach KW - decision-making process TI - Banks and Corporate Income Taxation: A Review ER - TY - CONF AB - Service Level Agreements are essential tools enabling clients and telco operators to specify required quality of service. The 5GTANGO NFV platform enables SLAs through policies and custom service lifecycle management components. This allows the operator to trigger certain lifecycle management events for a service, and the network service developer to define how to execute such events (e.g., how to scale). In this demo we will demonstrate this unique 5GTANGO concept using an elastic proxy service supported by a high availability SLA enforced through a range of traffic regimes. AU - Soenen, Thomas AU - Vicens, Felipe AU - Bonnet, José AU - Parada, Carlos AU - Kapassa, Evgenia AU - Touloupou, Marious AU - Fotopulou, Eleni AU - Zafeiropoulos, Anastasios AU - Pol, Ana AU - Kolometsos, Stavros AU - Xilouris, George AU - Alemany, Pol AU - Vilalta, Ricard AU - Trakadas, Panos AU - Karkazis, Panos AU - Peuster, Manuel AU - Tavernier, Wouter ID - 15368 KW - 5G mobile communication KW - contracts KW - quality of service KW - telecommunication traffic KW - virtualisation KW - custom service lifecycle management components KW - lifecycle management events KW - network service developer KW - elastic proxy service KW - SLA-controlled proxy service KW - customisable MANO KW - operator policies KW - Service Level Agreements KW - unique 5G TANGO concept KW - 5G TANGO NFV platform KW - quality of service KW - traffic regimes KW - high availability SLA KW - Monitoring KW - Probes KW - Portals KW - Quality of service KW - Tools KW - Servers KW - Graphical user interfaces SN - 1573-0077 T2 - 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) TI - SLA-controlled Proxy Service Through Customisable MANO Supporting Operator Policies ER - TY - CONF AU - Müller, Marcel AU - Behnke, Daniel AU - Bök, Patrick-Benjamin AU - Peuster, Manuel AU - Schneider, Stefan Balthasar AU - Karl, Holger ID - 15369 T2 - IEEE 17th International Conference on Industrial Informatics (IEEE-INDIN) TI - 5G as Key Technology for Networked Factories: Application of Vertical-specific Network Services for Enabling Flexible Smart Manufacturing ER - 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 -