TY - THES A1 - Hesse, Günter T1 - A benchmark for enterprise stream processing architectures T1 - Ein Benchmark für Architekturen zur Datenstromverarbeitung im Unternehmenskontext N2 - Data stream processing systems (DSPSs) are a key enabler to integrate continuously generated data, such as sensor measurements, into enterprise applications. DSPSs allow to steadily analyze information from data streams, e.g., to monitor manufacturing processes and enable fast reactions to anomalous behavior. Moreover, DSPSs continuously filter, sample, and aggregate incoming streams of data, which reduces the data size, and thus data storage costs. The growing volumes of generated data have increased the demand for high-performance DSPSs, leading to a higher interest in these systems and to the development of new DSPSs. While having more DSPSs is favorable for users as it allows choosing the system that satisfies their requirements the most, it also introduces the challenge of identifying the most suitable DSPS regarding current needs as well as future demands. Having a solution to this challenge is important because replacements of DSPSs require the costly re-writing of applications if no abstraction layer is used for application development. However, quantifying performance differences between DSPSs is a difficult task. Existing benchmarks fail to integrate all core functionalities of DSPSs and lack tool support, which hinders objective result comparisons. Moreover, no current benchmark covers the combination of streaming data with existing structured business data, which is particularly relevant for companies. This thesis proposes a performance benchmark for enterprise stream processing called ESPBench. With enterprise stream processing, we refer to the combination of streaming and structured business data. Our benchmark design represents real-world scenarios and allows for an objective result comparison as well as scaling of data. The defined benchmark query set covers all core functionalities of DSPSs. The benchmark toolkit automates the entire benchmark process and provides important features, such as query result validation and a configurable data ingestion rate. To validate ESPBench and to ease the use of the benchmark, we propose an example implementation of the ESPBench queries leveraging the Apache Beam software development kit (SDK). The Apache Beam SDK is an abstraction layer designed for developing stream processing applications that is applied in academia as well as enterprise contexts. It allows to run the defined applications on any of the supported DSPSs. The performance impact of Apache Beam is studied in this dissertation as well. The results show that there is a significant influence that differs among DSPSs and stream processing applications. For validating ESPBench, we use the example implementation of the ESPBench queries developed using the Apache Beam SDK. We benchmark the implemented queries executed on three modern DSPSs: Apache Flink, Apache Spark Streaming, and Hazelcast Jet. The results of the study prove the functioning of ESPBench and its toolkit. ESPBench is capable of quantifying performance characteristics of DSPSs and of unveiling differences among systems. The benchmark proposed in this thesis covers all requirements to be applied in enterprise stream processing settings, and thus represents an improvement over the current state-of-the-art. N2 - Data Stream Processing Systems (DSPSs) sind eine Schlüsseltechnologie, um kontinuierlich generierte Daten, wie beispielsweise Sensormessungen, in Unternehmensanwendungen zu integrieren. Die durch DSPSs ermöglichte permanente Analyse von Datenströmen kann dabei zur Überwachung von Produktionsprozessen genutzt werden, um möglichst zeitnah auf ungewollte Veränderungen zu reagieren. Darüber hinaus filtern, sampeln und aggregieren DSPSs einkommende Daten, was die Datengröße reduziert und so auch etwaige Kosten für die Datenspeicherung. Steigende Datenvolumen haben in den letzten Jahren den Bedarf für performante DSPSs steigen lassen, was zur Entwicklung neuer DSPSs führte. Während eine große Auswahl an verfügbaren Systemen generell gut für Nutzer ist, stellt es potentielle Anwender auch vor die Herausforderung, das für aktuelle und zukünftige Anforderungen passendste DSPS zu identifizieren. Es ist wichtig, eine Lösung für diese Herausforderung zu haben, da das Austauschen von einem DSPS zu teuren Anpassungen oder Neuentwicklungen der darauf laufenden Anwendungen erfordert, falls für deren Entwicklung keine Abstraktionsschicht verwendet wurde. Das quantitative Vergleichen von DSPSs ist allerdings eine schwierige Aufgabe. Existierende Benchmarks decken nicht alle Kernfunktionalitäten von DSPSs ab und haben keinen oder unzureichenden Tool-Support, was eine objektive Ergebnisberechnung hinsichtlich der Performanz erschwert. Zudem beinhaltet kein Benchmark die Integration von Streamingdaten und strukturierten Geschäftsdaten, was ein besonders für Unternehmen relevantes Szenario ist. Diese Dissertation stellt ESPBench vor, einen neuen Benchmark für Stream Processing-Szenarien im Unternehmenskontext. Der geschäftliche Kontext wird dabei durch die Verbindung von Streamingdaten und Geschäftsdaten dargestellt. Das Design von ESPBench repräsentiert Szenarien der realen Welt, stellt die objektive Berechnung von Benchmarkergebnissen sicher und erlaubt das Skalieren über Datencharakteristiken. Das entwickelte Toolkit des Benchmarks stellt wichtige Funktionalitäten bereit, wie beispielsweise die Automatisierung den kompletten Benchmarkprozesses sowie die Überprüfung der Abfrageergebnisse hinsichtlich ihrer Korrektheit. Um ESPBench zu validieren und die Anwendung weiter zu vereinfachen, haben wir eine Beispielimplementierung der Queries veröffentlicht. Die Implementierung haben wir mithilfe des in Industrie und Wissenschaft eingesetzten Softwareentwicklungsbaukastens Apache Beam durchgeführt, der es ermöglicht, entwickelte Anwendungen auf allen unterstützten DSPSs auszuführen. Den Einfluss auf die Performanz des Verwendens von Apache Beam wird dabei ebenfalls in dieser Arbeit untersucht. Weiterhin nutzen wir die veröffentlichte Beispielimplementierung der Queries um drei moderne DSPSs mit ESPBench zu untersuchen: Apache Flink, Apache Spark Streaming und Hazelcast Jet. Der Ergebnisse der Studie verdeutlichen die Funktionsfähigkeit von ESPBench und dessen Toolkit. ESPBench befähigt Performanzcharakteristiken von DSPSs zu quantifizieren und Unterschiede zwischen Systemen aufzuzeigen. Der in dieser Dissertation vorgestellte Benchmark erfüllt alle Anforderungen, um in Stream Processing-Szenarien im Unternehmenskontext eingesetzt zu werden und stellt somit eine Verbesserung der aktuellen Situation dar. KW - stream processing KW - performance KW - benchmarking KW - dsps KW - espbench KW - benchmark KW - Performanz KW - Datenstromverarbeitung KW - Benchmark Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-566000 ER - TY - GEN A1 - Galke, Lukas A1 - Gerstenkorn, Gunnar A1 - Scherp, Ansgar T1 - A case atudy of closed-domain response suggestion with limited training data T2 - Database and Expert Systems Applications : DEXA 2018 Iinternational workshops N2 - We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation. Y1 - 2018 SN - 978-3-319-99133-7 SN - 978-3-319-99132-0 U6 - https://doi.org/10.1007/978-3-319-99133-7_18 SN - 1865-0929 SN - 1865-0937 VL - 903 SP - 218 EP - 229 PB - Springer CY - Berlin ER - TY - JOUR A1 - Wuttke, Matthias A1 - Li, Yong A1 - Li, Man A1 - Sieber, Karsten B. A1 - Feitosa, Mary F. A1 - Gorski, Mathias A1 - Tin, Adrienne A1 - Wang, Lihua A1 - Chu, Audrey Y. A1 - Hoppmann, Anselm A1 - Kirsten, Holger A1 - Giri, Ayush A1 - Chai, Jin-Fang A1 - Sveinbjornsson, Gardar A1 - Tayo, Bamidele O. A1 - Nutile, Teresa A1 - Fuchsberger, Christian A1 - Marten, Jonathan A1 - Cocca, Massimiliano A1 - Ghasemi, Sahar A1 - Xu, Yizhe A1 - Horn, Katrin A1 - Noce, Damia A1 - Van der Most, Peter J. A1 - Sedaghat, Sanaz A1 - Yu, Zhi A1 - Akiyama, Masato A1 - Afaq, Saima A1 - Ahluwalia, Tarunveer Singh A1 - Almgren, Peter A1 - Amin, Najaf A1 - Arnlov, Johan A1 - Bakker, Stephan J. L. A1 - Bansal, Nisha A1 - Baptista, Daniela A1 - Bergmann, Sven A1 - Biggs, Mary L. A1 - Biino, Ginevra A1 - Boehnke, Michael A1 - Boerwinkle, Eric A1 - Boissel, Mathilde A1 - Böttinger, Erwin A1 - Boutin, Thibaud S. A1 - Brenner, Hermann A1 - Brumat, Marco A1 - Burkhardt, Ralph A1 - Butterworth, Adam S. A1 - Campana, Eric A1 - Campbell, Archie A1 - Campbell, Harry A1 - Canouil, Mickael A1 - Carroll, Robert J. A1 - Catamo, Eulalia A1 - Chambers, John C. A1 - Chee, Miao-Ling A1 - Chee, Miao-Li A1 - Chen, Xu A1 - Cheng, Ching-Yu A1 - Cheng, Yurong A1 - Christensen, Kaare A1 - Cifkova, Renata A1 - Ciullo, Marina A1 - Concas, Maria Pina A1 - Cook, James P. A1 - Coresh, Josef A1 - Corre, Tanguy A1 - Sala, Cinzia Felicita A1 - Cusi, Daniele A1 - Danesh, John A1 - Daw, E. Warwick A1 - De Borst, Martin H. A1 - De Grandi, Alessandro A1 - De Mutsert, Renee A1 - De Vries, Aiko P. J. A1 - Degenhardt, Frauke A1 - Delgado, Graciela A1 - Demirkan, Ayse A1 - Di Angelantonio, Emanuele A1 - Dittrich, Katalin A1 - Divers, Jasmin A1 - Dorajoo, Rajkumar A1 - Eckardt, Kai-Uwe A1 - Ehret, Georg A1 - Elliott, Paul A1 - Endlich, Karlhans A1 - Evans, Michele K. A1 - Felix, Janine F. A1 - Foo, Valencia Hui Xian A1 - Franco, Oscar H. A1 - Franke, Andre A1 - Freedman, Barry I. A1 - Freitag-Wolf, Sandra A1 - Friedlander, Yechiel A1 - Froguel, Philippe A1 - Gansevoort, Ron T. A1 - Gao, He A1 - Gasparini, Paolo A1 - Gaziano, J. Michael A1 - Giedraitis, Vilmantas A1 - Gieger, Christian A1 - Girotto, Giorgia A1 - Giulianini, Franco A1 - Gogele, Martin A1 - Gordon, Scott D. A1 - Gudbjartsson, Daniel F. A1 - Gudnason, Vilmundur A1 - Haller, Toomas A1 - Hamet, Pavel A1 - Harris, Tamara B. A1 - Hartman, Catharina A. A1 - Hayward, Caroline A1 - Hellwege, Jacklyn N. A1 - Heng, Chew-Kiat A1 - Hicks, Andrew A. A1 - Hofer, Edith A1 - Huang, Wei A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Indridason, Olafur S. A1 - Ingelsson, Erik A1 - Ising, Marcus A1 - Jaddoe, Vincent W. V. A1 - Jakobsdottir, Johanna A1 - Jonas, Jost B. A1 - Joshi, Peter K. A1 - Josyula, Navya Shilpa A1 - Jung, Bettina A1 - Kahonen, Mika A1 - Kamatani, Yoichiro A1 - Kammerer, Candace M. A1 - Kanai, Masahiro A1 - Kastarinen, Mika A1 - Kerr, Shona M. A1 - Khor, Chiea-Chuen A1 - Kiess, Wieland A1 - Kleber, Marcus E. A1 - Koenig, Wolfgang A1 - Kooner, Jaspal S. A1 - Korner, Antje A1 - Kovacs, Peter A1 - Kraja, Aldi T. A1 - Krajcoviechova, Alena A1 - Kramer, Holly A1 - Kramer, Bernhard K. A1 - Kronenberg, Florian A1 - Kubo, Michiaki A1 - Kuhnel, Brigitte A1 - Kuokkanen, Mikko A1 - Kuusisto, Johanna A1 - La Bianca, Martina A1 - Laakso, Markku A1 - Lange, Leslie A. A1 - Langefeld, Carl D. A1 - Lee, Jeannette Jen-Mai A1 - Lehne, Benjamin A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Lim, Su-Chi A1 - Lind, Lars A1 - Lindgren, Cecilia M. A1 - Liu, Jun A1 - Liu, Jianjun A1 - Loeffler, Markus A1 - Loos, Ruth J. F. A1 - Lucae, Susanne A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Magi, Reedik A1 - Magnusson, Patrik K. E. A1 - Mahajan, Anubha A1 - Martin, Nicholas G. A1 - Martins, Jade A1 - Marz, Winfried A1 - Mascalzoni, Deborah A1 - Matsuda, Koichi A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Metspalu, Andres A1 - Mikaelsdottir, Evgenia K. A1 - Milaneschi, Yuri A1 - Miliku, Kozeta A1 - Mishra, Pashupati P. A1 - Program, V. A. Million Veteran A1 - Mohlke, Karen L. A1 - Mononen, Nina A1 - Montgomery, Grant W. A1 - Mook-Kanamori, Dennis O. A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nalls, Mike A. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - Noordam, Raymond A1 - Olafsson, Isleifur A1 - Oldehinkel, Albertine J. A1 - Orho-Melander, Marju A1 - Ouwehand, Willem H. A1 - Padmanabhan, Sandosh A1 - Palmer, Nicholette D. A1 - Palsson, Runolfur A1 - Penninx, Brenda W. J. H. A1 - Perls, Thomas A1 - Perola, Markus A1 - Pirastu, Mario A1 - Pirastu, Nicola A1 - Pistis, Giorgio A1 - Podgornaia, Anna I. A1 - Polasek, Ozren A1 - Ponte, Belen A1 - Porteous, David J. A1 - Poulain, Tanja A1 - Pramstaller, Peter P. A1 - Preuss, Michael H. A1 - Prins, Bram P. A1 - Province, Michael A. A1 - Rabelink, Ton J. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Reilly, Dermot F. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Ridker, Paul M. A1 - Rivadeneira, Fernando A1 - Rizzi, Federica A1 - Roberts, David J. A1 - Robino, Antonietta A1 - Rossing, Peter A1 - Rudan, Igor A1 - Rueedi, Rico A1 - Ruggiero, Daniela A1 - Ryan, Kathleen A. A1 - Saba, Yasaman A1 - Sabanayagam, Charumathi A1 - Salomaa, Veikko A1 - Salvi, Erika A1 - Saum, Kai-Uwe A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Ben Schottker, A1 - Schulz, Christina-Alexandra A1 - Schupf, Nicole A1 - Shaffer, Christian M. A1 - Shi, Yuan A1 - Smith, Albert V. A1 - Smith, Blair H. A1 - Soranzo, Nicole A1 - Spracklen, Cassandra N. A1 - Strauch, Konstantin A1 - Stringham, Heather M. A1 - Stumvoll, Michael A1 - Svensson, Per O. A1 - Szymczak, Silke A1 - Tai, E-Shyong A1 - Tajuddin, Salman M. A1 - Tan, Nicholas Y. Q. A1 - Taylor, Kent D. A1 - Teren, Andrej A1 - Tham, Yih-Chung A1 - Thiery, Joachim A1 - Thio, Chris H. L. A1 - Thomsen, Hauke A1 - Thorleifsson, Gudmar A1 - Toniolo, Daniela A1 - Tonjes, Anke A1 - Tremblay, Johanne A1 - Tzoulaki, Ioanna A1 - Uitterlinden, Andre G. A1 - Vaccargiu, Simona A1 - Van Dam, Rob M. A1 - Van der Harst, Pim A1 - Van Duijn, Cornelia M. A1 - Edward, Digna R. Velez A1 - Verweij, Niek A1 - Vogelezang, Suzanne A1 - Volker, Uwe A1 - Vollenweider, Peter A1 - Waeber, Gerard A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Wang, Ya Xing A1 - Wang, Chaolong A1 - Waterworth, Dawn M. A1 - Bin Wei, Wen A1 - White, Harvey A1 - Whitfield, John B. A1 - Wild, Sarah H. A1 - Wilson, James F. A1 - Wojczynski, Mary K. A1 - Wong, Charlene A1 - Wong, Tien-Yin A1 - Xu, Liang A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Weihua A1 - Zonderman, Alan B. A1 - Rotter, Jerome I. A1 - Bochud, Murielle A1 - Psaty, Bruce M. A1 - Vitart, Veronique A1 - Wilson, James G. A1 - Dehghan, Abbas A1 - Parsa, Afshin A1 - Chasman, Daniel I. A1 - Ho, Kevin A1 - Morris, Andrew P. A1 - Devuyst, Olivier A1 - Akilesh, Shreeram A1 - Pendergrass, Sarah A. A1 - Sim, Xueling A1 - Boger, Carsten A. A1 - Okada, Yukinori A1 - Edwards, Todd L. A1 - Snieder, Harold A1 - Stefansson, Kari A1 - Hung, Adriana M. A1 - Heid, Iris M. A1 - Scholz, Markus A1 - Teumer, Alexander A1 - Kottgen, Anna A1 - Pattaro, Cristian T1 - A catalog of genetic loci associated with kidney function from analyses of a million individuals JF - Nature genetics N2 - Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research. Y1 - 2019 U6 - https://doi.org/10.1038/s41588-019-0407-x SN - 1061-4036 SN - 1546-1718 VL - 51 IS - 6 SP - 957 EP - + PB - Nature Publ. Group CY - New York ER - TY - GEN A1 - Halfpap, Stefan A1 - Schlosser, Rainer T1 - A Comparison of Allocation Algorithms for Partially Replicated Databases T2 - 2019 IEEE 35th International Conference on Data Engineering (ICDE) N2 - Increasing demand for analytical processing capabilities can be managed by replication approaches. However, to evenly balance the replicas' workload shares while at the same time minimizing the data replication factor is a highly challenging allocation problem. As optimal solutions are only applicable for small problem instances, effective heuristics are indispensable. In this paper, we test and compare state-of-the-art allocation algorithms for partial replication. By visualizing and exploring their (heuristic) solutions for different benchmark workloads, we are able to derive structural insights and to detect an algorithm's strengths as well as its potential for improvement. Further, our application enables end-to-end evaluations of different allocations to verify their theoretical performance. Y1 - 2019 SN - 978-1-5386-7474-1 SN - 978-1-5386-7475-8 U6 - https://doi.org/10.1109/ICDE.2019.00226 SN - 1084-4627 SN - 2375-026X SN - 1063-6382 SP - 2008 EP - 2011 PB - IEEE CY - New York ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Kayem, Anne V. D. M. A1 - Cheng, Feng A1 - Meinel, Christoph T1 - A cyber risk based moving target defense mechanism for microservice architectures T2 - IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom) N2 - Microservice Architectures (MSA) structure applications as a collection of loosely coupled services that implement business capabilities. The key advantages of MSA include inherent support for continuous deployment of large complex applications, agility and enhanced productivity. However, studies indicate that most MSA are homogeneous, and introduce shared vulnerabilites, thus vulnerable to multi-step attacks, which are economics-of-scale incentives to attackers. In this paper, we address the issue of shared vulnerabilities in microservices with a novel solution based on the concept of Moving Target Defenses (MTD). Our mechanism works by performing risk analysis against microservices to detect and prioritize vulnerabilities. Thereafter, security risk-oriented software diversification is employed, guided by a defined diversification index. The diversification is performed at runtime, leveraging both model and template based automatic code generation techniques to automatically transform programming languages and container images of the microservices. Consequently, the microservices attack surfaces are altered thereby introducing uncertainty for attackers while reducing the attackability of the microservices. Our experiments demonstrate the efficiency of our solution, with an average success rate of over 70% attack surface randomization. KW - Security Risk Assessment KW - Security Metrics KW - Moving Target Defense KW - Microservices Security KW - Application Container Security Y1 - 2018 SN - 978-1-7281-1141-4 U6 - https://doi.org/10.1109/BDCloud.2018.00137 SN - 2158-9178 SP - 932 EP - 939 PB - Institute of Electrical and Electronics Engineers CY - Los Alamitos ER - TY - THES A1 - Krentz, Konrad-Felix T1 - A Denial-of-Sleep-Resilient Medium Access Control Layer for IEEE 802.15.4 Networks T1 - Eine Denial-of-Sleep-Resiliente Mediumzugriffsschicht für IEEE-802.15.4-Netzwerke N2 - With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found. The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack. N2 - Mit dem Aufkommen des Internets der Dinge (IoT), werden immer mehr batteriebetriebene und energieerntende Geräte in diversen Anwendungsbereichen eingesetzt, etwa in der Heimautomatisierung, Präzisionslandwirtschaft, Industrieautomatisierung oder intelligenten Stadt. In diesem Kontext stellen sogenannte Denial-of-Sleep-Angriffe eine immer kritischer werdende Bedrohung dar. Solche Angriffe halten batteriebetriebene, energieerntende oder anderweitig energiebeschränkte Geräte zeitweise oder chronisch ab, in energiesparende Schlafmodi überzugehen. Erfolgreiche Denial-of-Sleep-Angriffe führen zumindest zu einer langen Ausfallzeit der betroffenen Geräte. Um betroffene batteriebetriebene Geräte wieder in Betrieb zu nehmen, müssen zudem deren Batterien gewechselt werden. Dies ist mühsam oder eventuell sogar unmöglich, z.B. wenn solche Geräte an unzugänglichen Orten installiert sind. Obwohl die Forschungsgemeinschaft bereits viele Denial-of-Sleep-Abwehrmechanismen vorgeschlagen hat, besitzen die meisten aktuellen IoT-Protokolle überhaupt keine Denial-of-Sleep-Abwehrmechanismen. Dies kann zum einen daran liegen, dass man des Problems noch nicht gewahr ist, aber zum anderen auch daran, dass viele Integrationsfragen bislang ungeklärt sind. Des Weiteren existieren bisher sowieso noch keine effektiven Abwehrmechanismen gegen bestimmte Denial-of-Sleep-Angriffe. Der Hauptbeitrag dieser Dissertation ist die Entwicklung einer Denial-of-Sleep-resilienten Mediumzugriffsschicht für IoT-Geräte, die via IEEE-802.15.4-Funkverbindungen kommunizieren. Die entwickelte Mediumzugriffsschicht besitzt zwei Hauptkomponenten. Die erste Hauptkomponente ist ein Denial-of-Sleep-resilientes Protokoll zur Etablierung von Sitzungsschlüsseln zwischen benachbarten IEEE-802.15.4-Knoten. Diese Sitzungsschlüssel dienen einerseits der grundlegenden Absicherung des Funkverkehrs und andererseits der Implementierung zusätzlicher Denial-of-Sleep-Abwehrmechanismen in der zweiten Hauptkomponente. Die zweite Hauptkomponente ist ein Denial-of-Sleep-resilientes Mediumzugriffsprotokoll. Bemerkenswert an diesem Mediumzugriffsprotokoll ist, dass es nicht nur neuartige Denial-of-Sleep-Abwehrmechanismen enthält, sondern auch dem Stand der Technik entsprechende Mechanismen zur Verringerung des Energieverbrauchs, zur Steigerung des Durchsatzes sowie zur Erhöhung der Zuverlässigkeit. Zusammenfassend widersteht bzw. mildert unsere Denial-of-Sleep-resiliente Mediumzugriffsschicht alle uns bekannten Denial-of-Sleep-Angriffe, die gegen sie gefahren werden können. Außerdem kann unsere Denial-of-Sleep-resiliente Mediumzugriffsschicht ohne Weiteres an Stelle von IEEE-802.15.4-konformen Mediumzugriffsschichten eingesetzt werden. Dies zeigen wir durch die nahtlose Integration unserer Mediumzugriffsschicht in den Netzwerk-Stack des Betriebssystems Contiki-NG. KW - medium access control KW - denial of sleep KW - internet of things KW - Mediumzugriffskontrolle KW - Schlafentzugsangriffe KW - Internet der Dinge Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-439301 ER - TY - JOUR A1 - Ihde, Sven A1 - Pufahl, Luise A1 - Völker, Maximilian A1 - Goel, Asvin A1 - Weske, Mathias T1 - A framework for modeling and executing task BT - specific resource allocations in business processes JF - Computing : archives for informatics and numerical computation N2 - As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach. KW - Process Execution KW - Business Process Management KW - Resource Allocation KW - Resource Management KW - Activity-oriented Optimization Y1 - 2022 U6 - https://doi.org/10.1007/s00607-022-01093-2 SN - 0010-485X SN - 1436-5057 VL - 104 SP - 2405 EP - 2429 PB - Springer CY - Wien ER - TY - GEN A1 - Gonzalez-Lopez, Fernanda A1 - Pufahl, Luise T1 - A Landscape for Case Models T2 - Enterprise, Business-Process and Information Systems Modeling N2 - Case Management is a paradigm to support knowledge-intensive processes. The different approaches developed for modeling these types of processes tend to result in scattered models due to the low abstraction level at which the inherently complex processes are therein represented. Thus, readability and understandability is more challenging than that of traditional process models. By reviewing existing proposals in the field of process overviews and case models, this paper extends a case modeling language - the fragment-based Case Management (fCM) language - with the goal of modeling knowledge-intensive processes from a higher abstraction level - to generate a so-called fCM landscape. This proposal is empirically evaluated via an online experiment. Results indicate that interpreting an fCM landscape might be more effective and efficient than interpreting an informationally equivalent case model. KW - Case Management KW - Process landscape KW - Process map KW - Process architecture KW - Process model Y1 - 2019 SN - 978-3-030-20618-5 SN - 978-3-030-20617-8 U6 - https://doi.org/10.1007/978-3-030-20618-5_6 SN - 1865-1348 VL - 352 SP - 87 EP - 102 PB - Springer CY - Berlin ER - TY - BOOK A1 - Schneider, Sven A1 - Lambers, Leen A1 - Orejas, Fernando T1 - A logic-based incremental approach to graph repair T1 - Ein logikbasierter inkrementeller Ansatz für Graphreparatur N2 - Graph repair, restoring consistency of a graph, plays a prominent role in several areas of computer science and beyond: For example, in model-driven engineering, the abstract syntax of models is usually encoded using graphs. Flexible edit operations temporarily create inconsistent graphs not representing a valid model, thus requiring graph repair. Similarly, in graph databases—managing the storage and manipulation of graph data—updates may cause that a given database does not satisfy some integrity constraints, requiring also graph repair. We present a logic-based incremental approach to graph repair, generating a sound and complete (upon termination) overview of least-changing repairs. In our context, we formalize consistency by so-called graph conditions being equivalent to first-order logic on graphs. We present two kind of repair algorithms: State-based repair restores consistency independent of the graph update history, whereas deltabased (or incremental) repair takes this history explicitly into account. Technically, our algorithms rely on an existing model generation algorithm for graph conditions implemented in AutoGraph. Moreover, the delta-based approach uses the new concept of satisfaction (ST) trees for encoding if and how a graph satisfies a graph condition. We then demonstrate how to manipulate these STs incrementally with respect to a graph update. N2 - Die Reparatur von Graphen, die Wiederherstellung der Konsistenz eines Graphen, spielt in mehreren Bereichen der Informatik und darüber hinaus eine herausragende Rolle: Beispielsweise wird in der modellgetriebenen Konstruktion die abstrakte Syntax von Modellen in der Regel mithilfe von Graphen kodiert. Flexible Bearbeitungsvorgänge erstellen vorübergehend inkonsistente Diagramme, die kein gültiges Modell darstellen, und erfordern daher eine Reparatur des Diagramms. Auf ähnliche Weise können Aktualisierungen in Graphendatenbanken - die das Speichern und Bearbeiten von Graphendaten verwalten - dazu führen, dass eine bestimmte Datenbank einige Integritätsbeschränkungen nicht erfüllt und auch eine Graphreparatur erforderlich macht. Wir präsentieren einen logikbasierten inkrementellen Ansatz für die Graphreparatur, der eine solide und vollständige (nach Beendigung) Übersicht über die am wenigsten verändernden Reparaturen erstellt. In unserem Kontext formalisieren wir die Konsistenz mittels sogenannten Graphbedingungen die der Logik erster Ordnung in Graphen entsprechen. Wir stellen zwei Arten von Reparaturalgorithmen vor: Die zustandsbasierte Reparatur stellt die Konsistenz unabhängig vom Verlauf der Graphänderung wieder her, während die deltabasierte (oder inkrementelle) Reparatur diesen Verlauf explizit berücksichtigt. Technisch stützen sich unsere Algorithmen auf einen vorhandenen Modellgenerierungsalgorithmus für in AutoGraph implementierte Graphbedingungen. Darüber hinaus verwendet der deltabasierte Ansatz das neue Konzept der Erfüllungsbäume (STs) zum Kodieren, ob und wie ein Graph eine Graphbedingung erfüllt. Wir zeigen dann, wie diese STs in Bezug auf eine Graphaktualisierung inkrementell manipuliert werden. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 126 KW - nested graph conditions KW - graph repair KW - model repair KW - consistency restoration KW - verschachtelte Graphbedingungen KW - Graphreparatur KW - Modellreparatur KW - Konsistenzrestauration Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427517 SN - 978-3-86956-462-3 SN - 1613-5652 SN - 2191-1665 IS - 126 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - de Paula, Danielly A1 - Marx, Carolin A1 - Wolf, Ella A1 - Dremel, Christian A1 - Cormican, Kathryn A1 - Uebernickel, Falk T1 - A managerial mental model to drive innovation in the context of digital transformation JF - Industry and innovation N2 - Industry 4.0 is transforming how businesses innovate and, as a result, companies are spearheading the movement towards 'Digital Transformation'. While some scholars advocate the use of design thinking to identify new innovative behaviours, cognition experts emphasise the importance of top managers in supporting employees to develop these behaviours. However, there is a dearth of research in this domain and companies are struggling to implement the required behaviours. To address this gap, this study aims to identify and prioritise behavioural strategies conducive to design thinking to inform the creation of a managerial mental model. We identify 20 behavioural strategies from 45 interviewees with practitioners and educators and combine them with the concepts of 'paradigm-mindset-mental model' from cognition theory. The paper contributes to the body of knowledge by identifying and prioritising specific behavioural strategies to form a novel set of survival conditions aligned to the new industrial paradigm of Industry 4.0. KW - Strategic cognition KW - mental models KW - industry 4.0 KW - digital transformation KW - design thinking Y1 - 2022 U6 - https://doi.org/10.1080/13662716.2022.2072711 SN - 1366-2716 SN - 1469-8390 PB - Routledge, Taylor & Francis Group CY - Abingdon ER -