piwik-script

Intern
    Chair of Computer Science II - Software Engineering

    Publications

    Publications of Software-Engineering Group / Descartes Research Group

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    [ 2021 ] [ 2020 ] [ 2019 ] [ 2018 ] [ 2017 ] [ 2016 ] [ 2015 ] [ 2014 ] [ 2013 ] [ 2012 ] [ 2011 ] [ 2010 ] [ 2009 ] [ 2008 ] [ 2007 ] [ 2006 ] [ 2005 ] [ 2004 ] [ 2003 ] [ 2002 ] [ 2001 ] [ 1999 ]

    2021 [ nach oben ]

    • A Machine Learning-based Workflow for Automatic Detection of Anomalies in Machine Tools. M. Züfle; F. Moog; V. Lesch; C. Krupitzer; S. Kounev; in ISA Transactions (2021).
      (in press)
       
    • SuanMing: Explainable Pre... - Download
      SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. J. Grohmann; M. Straesser; A. Chalbani; S. Eismann; Y. Arian; N. Herbst; N. Peretz; S. Kounev; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
      Acceptance Rate: 29%
       
    • Recommendations for Data-Driven Degradation Estimation with Case Studies from Manufacturing and Dry-Bulk Shipping. N. Finke; M. Mohr; A. Lontke; M. Züfle; S. Kounev; R. Möller; in RCIS (2021). 189–204.
       
    • Serverless Applications:W... - Download
      Serverless Applications:Why, When, and How?. S. Eismann; S. Joel; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; in IEEE Software (2021). 38(1) 32–39.
       
    • A Comparison of Mechanism... - Download
      A Comparison of Mechanisms for Compensating Negative Impacts of System Integration. V. Lesch; C. Krupitzer; K. Stubenrauch; N. Keil; C. Becker; S. Kounev; M. Segata; in Future Generation Computer Systems (2021). 116 117–131.
       
    • Libra: A Benchmark for Ti... - Download
      Libra: A Benchmark for Time Series Forecasting Methods. A. Bauer; M. Züfle; S. Eismann; J. Grohmann; N. Herbst; S. Kounev; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
       
    • Performance Impact Analysis of Securing MQTT Using TLS. T. Prantl; L. Iffländer; S. Herrnleben; S. Engel; S. Kounev; C. Krupitzer; in 2021 ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
       
    • Towards a Group Encryption Scheme Benchmark: A View on Centralized Schemes with focus on IoT. T. Prantl; P. Ten; L. Iffländer; S. Herrnleben; A. Dmitrenko; S. Kounev; C. Krupitzer; in 2021 ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
       
    • Utility-based Vehicle Rou... - Download
      Utility-based Vehicle Routing Integrating User Preferences. V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; in Proceedings of 3rd International Workshop on Pervasive Computing for Vehicular Systems (PerVehicle), 2021 (2021).
      To appear
       
    • A Simulation-based Optimi... - Download
      A Simulation-based Optimization Framework for Online Adaptation of Networks. S. Herrnleben; J. Grohmann; P. Rygielski; V. Lesch; C. Krupitzer; S. Kounev; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools), H. Song, D. Jiang (Hrsg.) (2021). 513–532.
       
    • SPEC Research Group Newsl... - Download
      SPEC Research Group Newsletter, vol. 3 no. 2. S. Kounev; A. van Hoorn; A. Bauer; (2021, April).
      Published by Standard Performance Evaluation Corporation (SPEC)
       
    • Auswirkungen der COVID-19-Pandemie auf Sportlerinnen und Sportler in Deutschland. C. Zinner; M. Matzka; R. Leppich; S. Kounev; H.-C. Holmberg; B. Sperlich; in 53. asp Jahrestagung (2021).
       
    • SARDE: A Framework for Co... - Download
      SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. J. Grohmann; S. Eismann; A. Bauer; S. Spinner; J. Blum; N. Herbst; S. Kounev; in ACM Transactions on Autonomous and Adaptive Systems (2021). 15(2)
       
    • Establishing a cardiac training group for patients with heart failure: the “HIP-in-Würzburg” study. G. Güder; J. Wilkesmann; N. Scholz; R. Leppich; P. Düking; B. Sperlich; C. Rost; S. Frantz; C. Morbach; F. Sahiti; others; in Clinical Research in Cardiology (2021). 1–10.
       
    • A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. M. Züfle; J. Agne; J. Grohmann; I. Dörtoluk; S. Kounev; in Proceedings of the 21st IEEE IES International Conference on Industrial Informatics (2021).
      (to appear)
       
    • Buzzy: Towards Realistic ... - Download
      Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads. J. Domaschka; S. Eismann; M. Leznik; J. Grohmann; S. Kounev; D. Seybold; in Companion of the ACM/SPEC International Conference on Performance Engineering (2021). (Bd. ICPE ’21) 175–178.
       

    2020 [ nach oben ]

    • A Survey on Predictive Ma... - Download
      A Survey on Predictive Maintenance for Industry 4.0 C. Krupitzer; T. Wagenhals; M. Züfle; V. Lesch; D. Schäfer; A. Mozaffarin; J. Edinger; C. Becker; S. Kounev; (2020).
       
    • REACT: A Model-Based Runt... - Download
      REACT: A Model-Based Runtime Environment for Adapting Communication Systems. M. Pfannemüller; M. Breitbach; C. Krupitzer; M. Weckesser; C. Becker; B. Schmerl; A. Schürr; in Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020) (2020).
       
    • Optimizing Parametric Dep... - Download
      Optimizing Parametric Dependencies for Incremental Performance Model Extraction. S. Voneva; M. Mazkatli; J. Grohmann; A. Koziolek; in Companion of the 14th European Conference Software Architecture (ECSA 2020), H. Muccini, P. Avgeriou, B. Buhnova, J. Cámara, M. Caporuscio, M. Franzago, A. Koziolek, P. Scandurra, C. Trubiani, D. Weyns, U. Zdun (Hrsg.) (2020). (Bd. 1269) 228–240.
       
    • Evaluating the Performance of a State-of-the-Art Group-oriented Encryption Scheme for Dynamic Groups in an IoT Scenario. T. Prantl; P. Ten; L. Iffländer; A. Dmitrenko; S. Kounev; C. Krupitzer; in 2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2020).
      Acceptance Rate: 27%
       
    • Quantifying measurement q... - Download
      Quantifying measurement quality and load distribution in Tor. A. Greubel; S. Pohl; S. Kounev; in Proceedings of the 36th Annual Computer Security Applications Conference (ACSAC 2020) (2020).
       
    • An IoT Network Emulator f... - Download
      An IoT Network Emulator for Analyzing the Influence of Varying Network Quality. S. Herrnleben; R. Ailabouni; J. Grohmann; T. Prantl; C. Krupitzer; S. Kounev; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools) (2020).
       
    • Baloo: Measuring and Mode... - Download
      Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS. J. Grohmann; D. Seybold; S. Eismann; M. Leznik; S. Kounev; J. Domaschka; in 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2020). 1–8.
      Acceptance Rate: 27%
       
    • An Overview of Design Pat... - Download
      An Overview of Design Patterns for Self-Adaptive Systems in the Context of the Internet of Things. C. Krupitzer; T. Temizer; T. Prantl; C. Raibulet; in IEEE Access (2020).
       
    • A Framework for Time Seri... - Download
      A Framework for Time Series Preprocessing and History-based Forecasting Method Recommendation. M. Züfle; S. Kounev; in Proceedings of the 15th Conference on Computer Science and Information Systems (FedCSIS): Data Mining Competition of the International Symposium on Advanced Artificial Intelligence in Applications (2020).
       
    • Telescope: An Automatic F... - Download
      Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field. A. Bauer; M. Züfle; N. Herbst; S. Kounev; V. Curtef; in Proceedings of the 36th International Conference on Data Engineering (ICDE) (2020).
       
    • SIMPL: Secure IoT Managem... - Download
      SIMPL: Secure IoT Management Platform. T. Prantl; A. E. Ben Yahya; A. Dmitrienko; S. Kounev; F. Lipp; D. Hock; C. Rathfelder; M. Hofherr; in ITG Workshop on IT Security (ITSec) (2020).
       
    • Predicting Performance De... - Download
      Predicting Performance Degradations of Black-box Microservice Applications M. Straesser; (2020).
       
    • The impact of the German strategy for containment of Coronavirus SARS-CoV-2 on the training characteristics, physical activity, sleep of highly trained kayakers and canoeists: A retrospective observational study. C. Zinner; M. Matzka; R. Leppich; S. Kounev; H. Holmberg; B. Sperlich; in Frontiers in Sports and Active Living (2020). 2 127.
       
    • Elasticity of Cloud Platforms. N. Herbst; A. Bauer; S. Kounev; in Systems Benchmarking: For Scientists and Engineers, S. Kounev, K.-D. Lange, J. von Kistowski (Hrsg.) (2020). 319–340.
       
    • Survey and Experimental Comparison of RGB-D Indoor Robot Navigation Methods Supported by ROS and Their Expansion via Fusion with Wheel Odometry and IMU Data. F. Spiess; J. Friesslich; K. Tobias; S. Kounev; N. Strobel; in IJMERR, (P. R. (Chunhui) Yang, Hrsg.) (2020). 9(12) 1532–1540.
       
    • Incremental Calibration o... - Download
      Incremental Calibration of Architectural Performance Models with Parametric Dependencies. M. Mazkatli; D. Monschein; J. Grohmann; A. Koziolek; in 2020 IEEE International Conference on Software Architecture (ICSA 2020) (2020). 23–34.
       
    • Learning to Learn in Coll... - Download
      Learning to Learn in Collective Adaptive Systems: Mining Design Pattern for Data-driven Reasoning. M. D’Angelo; S. Ghahremani; S. Gerasimou; J. Grohmann; I. Nunes; S. Tomforde; E. Pournaras; in 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) (2020). 121–126.
       
    • Towards a Self-Aware Prediction of Critical States. M. Züfle; in Organic Computing: Doctoral Dissertation Colloquium 2020, S. Tomforde, C. Krupitzer (Hrsg.) (2020).
      (to appear)
       
    • A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. J. Grohmann; N. Herbst; A. Chalbani; Y. Arian; N. Peretz; S. Kounev; in Computers (2020). 9(1) 10.
       
    • Predicting the Costs of S... - Download
      Predicting the Costs of Serverless Workflows. S. Eismann; J. Grohmann; E. van Eyk; N. Herbst; S. Kounev; in Proceedings of the 2020 ACM/SPEC International Conference on Performance Engineering (ICPE) (2020). 265–276.
      Acceptance Rate: 23.4% (15/64)
       
    • Towards Self-Aware Multir... - Download
      Towards Self-Aware Multirotor Formations. D. Kaiser; V. Lesch; J. Rothe; M. Strohmeier; F. Spiess; C. Krupitzer; S. Montenegro; S. Kounev; in Computers (2020). 9(7)
      Special Issue on Self-Aware Computing
       
    • A Review of Serverless Us... - Download
      A Review of Serverless Use Cases and their Characteristics S. Eismann; J. Scheuner; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; (2020).
       
    • Toward a Framework for Self-Learning Adaptation Planning through Optimization. V. Lesch; in Organic Computing: Doctoral Dissertation Colloquium 2020 (2020).
      To appear
       
    • Predicting Failures by Means of Machine Learning Methods on the Example of an Industrial Press. J. Agne; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2020, März).
       
    • A Survey on Human Machine... - Download
      A Survey on Human Machine Interaction in Industry 4.0 C. Krupitzer; S. Müller; V. Lesch; M. Züfle; J. Edinger; A. Lemken; D. Schäfer; S. Kounev; C. Becker; (2020).
       
    • An Automated Forecasting ... - Download
      An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. A. Bauer; M. Züfle; J. Grohmann; N. Schmitt; N. Herbst; S. Kounev; in Proceedings of the ACM/SPEC International Conference on Performance Engineering (2020). 48–55.
       
    • A Concept for Crowd-sensed Prediction of Mobile Network Connectivity. S. Herrnleben; B. Zeidler; M. Züfle; C. Krupitzer; S. Kounev; in GI/ITG Workshop on Machine Learning in the Context of Communication Networks 2020 (2020).
       
    • Model-based Performance P... - Download
      Model-based Performance Predictions for SDN-based Networks: A Case Study. S. Herrnleben; P. Rygielski; J. Grohmann; S. Eismann; T. Hossfeld; S. Kounev; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020).
       
    • To Fail Or Not To Fail: P... - Download
      To Fail Or Not To Fail: Predicting Hard Disk Drive Failure Time Windows. M. Züfle; C. Krupitzer; F. Erhard; J. Grohmann; S. Kounev; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020). 19–36.
       
    • Introduction to the Speci... - Download
      Introduction to the Special Issue ``Applications in Self-Aware Computing Systems and their Evaluation’’. C. Krupitzer; B. Eberhardinger; I. Gerostathopoulos; C. Raibulet; (2020).
       
    • Microservices: A Performa... - Download
      Microservices: A Performance Tester’s Dream or Nightmare?. S. Eismann; C.-P. Bezemer; W. Shang; D. Okanovic; A. van Hoorn; in Proceedings of the 2020 ACM/SPEC International Conference on Performance Engineering (ICPE) (2020).
      Acceptance Rate: 23.4% (15/64)
       
    • Beyond Microbenchmarks: T... - Download
      Beyond Microbenchmarks: The SPEC-RG Vision for A Comprehensive Serverless Benchmark. E. van Eyk; J. Scheuner; S. Eismann; C. Abad; A. Iosup; in Companion of the 2020 ACM/SPEC International Conference on Performance Engineering (2020).
       
    • Methodological Principles... - Download
      Methodological Principles for Reproducible Performance Evaluation in Cloud Computing. A. V. Papadopoulos; L. Versluis; A. Bauer; N. Herbst; J. von Kistowski; A. Ali-Eldin; C. L. Abad; J. N. Amaral; P. Tuma; A. Iosup; in Software Engineering 2020, Fachtagung des GI-Fachbereichs Softwaretechnik, 24.-28. Februar 2020, Innsbruck, Austria, M. Felderer, W. Hasselbring, R. Rabiser, R. Jung (Hrsg.) (2020). (Bd. P-300) 93–94.
       
    • Time Series Forecasting for Self-Aware Systems. A. Bauer; M. Züfle; N. Herbst; A. Zehe; A. Hotho; S. Kounev; in Proceedings of the IEEE (2020). 108(7) 1068–1093.
       
    • SPEC Research Group Newsl... - Download
      SPEC Research Group Newsletter, vol. 3 no. 1. S. Kounev; A. van Hoorn; A. Bauer; N. Herbst; (2020, April).
      Published by Standard Performance Evaluation Corporation (SPEC)
       
    • Energy Efficiency Analysi... - Download
      Energy Efficiency Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite. N. Schmitt; J. Bucek; K.-D. Lange; S. Kounev; in Proceedings of the 11th ACM/SPEC International Conference on Performance Engineering (ICPE 2020) (2020).
       
    • Intra-individual physiological response of recreational runners to different training mesocycles: a randomized cross-over study. P. Düking; H.-C. Holmberg; P. Kunz; R. Leppich; B. Sperlich; in European Journal of Applied Physiology (2020). 1–9.
       

    2019 [ nach oben ]

    • A Concept for an Adaptive... - Download
      A Concept for an Adaptive Communication Middleware for Car-2-Cloud Applications. S. Herrnleben; (2019, April).
       
    • Towards Testing the Softw... - Download
      Towards Testing the Software Aging Behavior of Hypervisor Hypercall Interfaces. L. Beierlieb; L. Iffländer; A. Milenkoski; C. F. Goncalves; N. Antunes; S. Kounev; in 2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (2019).
       
    • Performance Oriented Dyna... - Download
      Performance Oriented Dynamic Bypassing for Intrusion Detection Systems. L. Iffländer; J. Stoll; N. Rawtani; V. Lesch; K.-D. Lange; S. Kounev; in Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering (2019). 159–166.
       
    • Integrating Statistical R... - Download
      Integrating Statistical Response Time Models in Architectural Performance Models. S. Eismann; J. Grohmann; J. Walter; J. von Kistowski; S. Kounev; in Proceedings of the 2019 IEEE International Conference on Software Architecture (ICSA) (2019). 71–80.
      Acceptance Rate: 21,9% (21/96)
       
    • Modeling of Aggregated Io... - Download
      Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud. F. Metzger; T. Hoßfeld; A. Bauer; S. Kounev; P. E. Heegaard; in Proceedings of the IEEE (2019). 107(4) 679–694.
       
    • SPEC Research Group Newsl... - Download
      SPEC Research Group Newsletter, vol. 2 no. 4. S. Kounev; A. van Hoorn; A. Bauer; N. Herbst; (2019, April).
      Published by Standard Performance Evaluation Corporation (SPEC)
       
    • Chamulteon: Coordinated A... - Download
      Chamulteon: Coordinated Auto-Scaling of Micro-Services. A. Bauer; V. Lesch; L. Versluis; A. Ilyushkin; N. Herbst; S. Kounev; in Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS) (2019).
       
    • Autonomic Forecasting Met... - Download
      Autonomic Forecasting Method Selection: Examination and Ways Ahead. M. Züfle; A. Bauer; V. Lesch; C. Krupitzer; N. Herbst; S. Kounev; V. Curtef; in Proceedings of the 16th IEEE International Conference on Autonomic Computing (ICAC) (2019).
       
    • TeaStore - A Micro-Servic... - Download
      TeaStore - A Micro-Service Application for Benchmarking, Modeling and Resource Management Research. S. Eismann; (2019, März).
       
    • Online Power Consumption ... - Download
      Online Power Consumption Estimation for Functions in Cloud Applications. N. Schmitt; L. Iffländer; A. Bauer; S. Kounev; in Proceedings of the 16th IEEE International Conference on Autonomic Computing (ICAC) (2019).
       
    • Der Weg vom Internet-der-Dinge zum Internet-der-denkenden-Dinge. S. Kounev; (2019, Juni).
       
    • Hands Off my Database: Ra... - Download
      Hands Off my Database: Ransomware Detection in Databases through Dynamic Analysis of Query Sequences L. Iffländer; A. Dmitrienko; C. Hagen; M. Jobst; S. Kounev; (2019).
       
    • From the Internet-of-Things to the Internet-of-Thinking-Things. S. Kounev; (2019, Juli).
       
    • Detecting Parametric Depe... - Download
      Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques. J. Grohmann; S. Eismann; S. Elflein; M. Mazkatli; J. von Kistowski; S. Kounev; in 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2019). 309–322.
      Acceptance Rate: 23.8% (29/122)
       
    • On Learning Parametric De... - Download
      On Learning Parametric Dependencies from Monitoring Data. J. Grohmann; S. Eismann; S. Kounev; in Proceedings of the 10th Symposium on Software Performance 2019 (SSP’19) (2019).
       
    • Online model learning for... - Download
      Online model learning for self-aware computing infrastructures. S. Spinner; J. Grohmann; S. Eismann; S. Kounev; in Journal of Systems and Software (2019). 147 1–16.
       
    • Towards Testing the Perfo... - Download
      Towards Testing the Performance Influence of Hypervisor Hypercall Interface Behavior. L. Beierlieb; L. Iffländer; S. Kounev; A. Milenkoski; in Proceedings of the 10th Symposium on Software Performance 2019 (SSP’19) (2019).
       
    • Monitorless: Predicting P... - Download
      Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning. J. Grohmann; P. K. Nicholson; J. O. Iglesias; S. Kounev; D. Lugones; in Proceedings of the 20th International Middleware Conference (2019). 149–162.
       
    • Methoden und Messverfahre... - Download
      Methoden und Messverfahren für Automatisches Skalieren in Elastischen Cloud Umgebungen. N. Herbst; (2019, Juni).
       
    • Kaa: Evaluating Elasticit... - Download
      Kaa: Evaluating Elasticity of Cloud-hosted DBMS. D. Seybold; S. Volpert; S. Wesner; A. Bauer; N. Herbst; J. Domaschka; in Proceedings of the 11th IEEE International Conference on Cloud Computing (CloudCom) (2019).
       
    • The SPEC-RG Reference Arc... - Download
      The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. E. van Eyk; J. Grohmann; S. Eismann; A. Bauer; L. Versluis; L. Toader; N. Schmitt; N. Herbst; C. L. Abad; A. Iosup; in IEEE Internet Computing (2019). 23(6) 7–18.
       
    • Best Practices for Time S... - Download
      Best Practices for Time Series Forecasting. A. Bauer; M. Züfle; N. Herbst; S. Kounev; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019).
       
    • Utilizing Clustering to O... - Download
      Utilizing Clustering to Optimize Resource Demand Estimation Approaches. J. Grohmann; S. Eismann; A. Bauer; M. Zuefle; N. Herbst; S. Kounev; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 134–139.
       
    • Artificial Intelligence in Medicine - From Data Collection to Prediction. M. Züfle; R. Leppich; (2019, November).
       
    • Designing a Generic Workflow for Frequency-based Feature Engineering of Sports Data Using Symbolic Fourier Approximation. F. Erhard; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2019, September).
       
    • Exploring the Limitations of Statistical Response Time Models in Architectural Performance Models. S. Trapp; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2019, Dezember).
       
    • An Approach for Domain-specific Data Extraction and Feature Engineering for Sports Data Analytics. T. Dreher; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2019, Oktober).
       
    • Erweiterung von Komponenten-basierten Performance Modellen für Micro-service Architekturen. L. Hick; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2019, März).
       
    • Towards Adaptive Car-to-C... - Download
      Towards Adaptive Car-to-Cloud Communication. S. Herrnleben; M. Pfannemüller; C. Krupitzer; S. Kounev; M. Segata; F. Fastnacht; M. Nigmann; in Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (2019).
       
    • Automation in Software Performance Engineering Based on a Declarative Specification of Concerns. J. C. Walter; (2019).
       
    • On Learning in Collective... - Download
      On Learning in Collective Self-Adaptive Systems: State of Practice and a 3D Framework. M. D’Angelo; S. Gerasimou; S. Ghahremani; J. Grohmann; I. Nunes; E. Pournaras; S. Tomforde; in Proceedings of the 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (2019). 13–24.
       
    • Die Mehrbelastung der Sicherheit im IoT mit neuen Techniken bewältigen. J. Stoll; L. Iffländer; (2019, April).
       
    • Chameleon: A Hybrid, Proa... - Download
      Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field. A. Bauer; (2019, Juni).
       
    • Towards Edge Benchmarking: A Methodology for Characterizing Edge Workloads. K. Tocze; N. Schmitt; I. Brandic; A. Aral; S. Nadjm-Tehrani; in Proceedings of Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf) as part of FAS*(IEEE ICAC/SASO) conferences companion (2019).
       
    • Improving the Energy Effi... - Download
      Improving the Energy Efficiency of IoT-Systems and its Software. N. Schmitt; in Organic Computing: Doctoral Dissertation Colloquium 2018, S. Tomforde, B. Sick (Hrsg.) (2019).
       
    • Emerging Self-Integration... - Download
      Emerging Self-Integration through Coordination of Autonomous Adaptive Systems. V. Lesch; C. Krupitzer; S. Tomforde; in Proceedings of the 4th IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W@ICAC/SASO 2019 (2019).
       
    • Multi-objective Optimisat... - Download
      Multi-objective Optimisation in Hybrid Collaborating Adaptive Systems. V. Lesch; C. Krupitzer; S. Tomforde; in Proceedings of the 7th edition in the Series on Autonomously Learning and Optimising Systems (SAOS), co-located with 32nd GI/ITG ARCS 2019 (2019).
       
    • The Organic Computing Doctoral Dissertation Colloquium: Status and Overview in 2019. C. Krupitzer; S. Tomforde; in Proceedings of the INFORMATIK 2019 (Workshop-Beiträge) (2019).
       
    • Please Obey My Plan: How ... - Download
      Please Obey My Plan: How to Optimise Decentralised Self-Adaptive Systems. V. Lesch; C. Krupitzer; S. Tomforde; (2019, April).
       
    • A Modular Simulation Fram... - Download
      A Modular Simulation Framework for Analyzing Platooning Coordination. C. Krupitzer; V. Lesch; M. Pfannemüller; C. Becker; M. Segata; in Proceedings of the 1st ACM Workshop on Technologies, mOdels, and Protocols for Cooperative Connected Cars (TOP-Cars), Colocated with ACM MobiHoc 2019 (2019).
       
    • WheelShare: Crowd-sensed ... - Download
      WheelShare: Crowd-sensed Surface Classification for Accessible Routing. J. Edinger; V. Raychoudhury; A. Hofmann; A. Wachner; C. Becker; C. Krupitzer; in Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (2019).
       
    • Planning as Optimization:... - Download
      Planning as Optimization: Dynamically Discovering Optimal Configurations for Runtime Situations. E. M. Fredericks; I. Gerostathopoulos; C. Krupitzer; T. Vogel; in Proceedings of the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2019 (2019).
       
    • A survey on adaptive auth... - Download
      A survey on adaptive authentication. P. Arias-Cabarcos; C. Krupitzer; C. Becker; in ACM Computing Surveys (2019). 52 Art. 80.
       
    • Beyond position-awareness... - Download
      Beyond position-awareness -- Extending a self-adaptive fall detection system. C. Krupitzer; T. Sztyler; J. Edinger; M. Breitbach; H. Stuckenschmidt; C. Becker; in Pervasive and Mobile Computing (2019). 58