This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-09-17 Creation time: 10-17-18 --- Number of references 8 inproceedings 2020-kirchhof-wowmom-ccncps 2020 8 31 internet-of-production, reflexes https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-kirchhof-wireless-mac-improvements.pdf IEEE Computer Society online International Symposium on a World of Wireless, Mobile and Multimedia Networks: Workshop on Communication, Computing, and Networking in Cyber Physical Systems (WoWMoM-CCNCPS'2020), August 31 - September 3, 2020, Cork, Ireland Cork, Ireland August 31 - September 3, 2020 10.1109/WoWMoM49955.2020.00068 1 Jörg ChristianKirchhof MartinSerror RenéGlebke KlausWehrle article 2020_niemietz_stamping Procedia Manufacturing 2020 7 11 49 61-68 Sharing data between companies throughout the supply chain is expected to be beneficial for product quality as well as for the economical savings in the manufacturing industry. To utilize the available data in the vision of an Internet of Production (IoP) a precise condition monitoring of manufacturing and production processes that facilitates the quantification of influences throughout the supply chain is inevitable. In this paper, we consider stamping processes in the context of an Internet of Production and the preliminaries for analytical models that utilize the ever-increasing available data. Three research objectives to cope with the amount of data and for a methodology to monitor, analyze and evaluate the influence of available data onto stamping processes have been identified: (i) State detection based on cyclic sensor signals, (ii) mapping of in- and output parameter variations onto process states, and (iii) models for edge and in-network computing approaches. After discussing state-of-the-art approaches to monitor stamping processes and the introduction of the fineblanking process as an exemplary stamping process, a research roadmap for an IoP enabling modeling framework is presented. Proceedings of the 8th International Conference on Through-Life Engineering Service (TESConf '19), October 27-29, 2019, Cleveland, OH, USA Stamping Process; Industry 4.0; Fine-blanking; Internet of production; Condition monitoring; Data analytics internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-niemietz-stamping-modelling.pdf Elsevier Cleveland, OH, USA October 27-29, 2019 2351-9789 10.1016/j.promfg.2020.06.012 1 PhilippNiemietz JanPennekamp IkeKunze DanielTrauth KlausWehrle ThomasBergs proceedings 2020-jacobs-euras 2020 6 29 15 Kai Jakobs, Dong-hyu Kim Mainz Publishers EURAS Contributions to Standardisation Research 9783958863552 KaiJakobs Dong-hyuKim inproceedings 2020_matzutt_coinprune 2020 6 24 298-306 Bitcoin was the first successful decentralized cryptocurrency and remains the most popular of its kind to this day. Despite the benefits of its blockchain, Bitcoin still faces serious scalability issues, most importantly its ever-increasing blockchain size. While alternative designs introduced schemes to periodically create snapshots and thereafter prune older blocks, already-deployed systems such as Bitcoin are often considered incapable of adopting corresponding approaches. In this work, we revise this popular belief and present CoinPrune, a snapshot-based pruning scheme that is fully compatible with Bitcoin. CoinPrune can be deployed through an opt-in velvet fork, i.e., without impeding the established Bitcoin network. By requiring miners to publicly announce and jointly reaffirm recent snapshots on the blockchain, CoinPrune establishes trust into the snapshots' correctness even in the presence of powerful adversaries. Our evaluation shows that CoinPrune reduces the storage requirements of Bitcoin already by two orders of magnitude today, with further relative savings as the blockchain grows. In our experiments, nodes only have to fetch and process 5 GiB instead of 230 GiB of data when joining the network, reducing the synchronization time on powerful devices from currently 5 h to 46 min, with even more savings for less powerful devices. blockchain; block pruning; synchronization; bootstrapping; scalability; velvet fork; Bitcoin mynedata; impact_digital; digital_campus https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-matzutt-coinprune.pdf https://coinprune.comsys.rwth-aachen.de IEEE Proceedings of the 19th IFIP Networking 2020 Conference (NETWORKING '20), June 22-26, 2020, Paris, France Paris, France NETWORKING 2020 June 22-26, 2020 978-3-903176-28-7 1 RomanMatzutt BenediktKalde JanPennekamp ArthurDrichel MartinHenze KlausWehrle inproceedings 2020-mann-ur-weldseamstudy 2020 6 https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-mann-weld-seam-geometry-control.pdf Proceedings of the 2020 Internal Conference on Ubiquitous Robots Internal Conference on Ubiquitous Robots June 22-26, 2020 10.1109/UR49135.2020.9144839 1 SamuelMann RenéGlebke IkeKunze DominikScheurenberg RahulSharma UweReisgen KlausWehrle DirkAbel article 2020_gleim_factDAG IEEE Internet of Things Journal 2020 4 14 7 4 3243-3253 In the production industry, the volume, variety and velocity of data as well as the number of deployed protocols increase exponentially due to the influences of IoT advances. While hundreds of isolated solutions exist to utilize this data, e.g., optimizing processes or monitoring machine conditions, the lack of a unified data handling and exchange mechanism hinders the implementation of approaches to improve the quality of decisions and processes in such an interconnected environment. The vision of an Internet of Production promises the establishment of a Worldwide Lab, where data from every process in the network can be utilized, even interorganizational and across domains. While numerous existing approaches consider interoperability from an interface and communication system perspective, fundamental questions of data and information interoperability remain insufficiently addressed. In this paper, we identify ten key issues, derived from three distinctive real-world use cases, that hinder large-scale data interoperability for industrial processes. Based on these issues we derive a set of five key requirements for future (IoT) data layers, building upon the FAIR data principles. We propose to address them by creating FactDAG, a conceptual data layer model for maintaining a provenance-based, directed acyclic graph of facts, inspired by successful distributed version-control and collaboration systems. Eventually, such a standardization should greatly shape the future of interoperability in an interconnected production industry. Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab internet-of-production https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf IEEE 2327-4662 10.1109/JIOT.2020.2966402 1 LarsGleim JanPennekamp MartinLiebenberg MelanieBuchsbaum PhilippNiemietz SimonKnape AlexanderEpple SimonStorms DanielTrauth ThomasBergs ChristianBrecher StefanDecker GerhardLakemeyer KlausWehrle inproceedings 2020-kosek-tcp-conformance 2020 3 30 maki https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-kosek-tcp-conformance-v2.pdf https://arxiv.org/abs/2002.05400 Springer Proceedings of the Passive and Active Measurement Conference (PAM '20) Eugene, Oregon, USA Passive and Active Measurement Conference (PAM 2020) 30.03.2020 - 31.03.2020 en https://doi.org/10.1007/978-3-030-44081-7_8 1 MikeKosek LeoBlöcher JanRüth TorstenZimmermann OliverHohlfeld article 2020-wehrle-digitalshadows Der Profilbereich "Information & Communication Technology" 2020 0179-079X 10.18154/RWTH-2021-02496 MatthiasJarke Wilvan der Aalst ChristianBrecher MatthiasBrockmann IstvánKoren GerhardLakemeyer BernhardRumpe GüntherSchuh KlausWehrle MartinaZiefle