Deutsch Intern
Chair of Computer Science II - Software Engineering

Publications

Publications of Software-Engineering Group / Descartes Research Group

This list contains dynamically generated, up-to-date list of publications with filtering possibilities.
Show publications grouped by research areas.

2024[ to top ]
  • Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. M. Stenger; A. Bauer; T. Prantl; R. Leppich; N. Hudson; K. Chard; I. Foster; S. Kounev; in J. Data and Information Quality (2024). 16(2)
  • Evaluation is key: a survey on evaluation measures for synthetic time series. M. Stenger; R. Leppich; I. Foster; S. Kounev; A. Bauer; in Journal of Big Data (2024). 11 66.
  • Patient-Centered Chronic Wound Care Mobile Apps: Systematic Identification, Analysis, and Assessment. T. Dege; B. Glatzel; V. Borst; F. Grän; S. Goller; C. Glatzel; M. Goebeler; A. Schmieder; in JMIR mHealth and uHealth (2024). 12
  • A Data-Driven Model for Range Sensors. F. Spiess; N. Strobel; T. Kaupp; S. Kounev; in International Journal of Semantic Computing (2024). 1–18.
  • Simulating Microservice-b...
    Simulating Microservice-based Architectures for Resilience Assessment Enriched by Authentic Container Orchestration. S. Frank; M. Straesser; L. Wagner; P. Haas; A. Hakamian; S. Kounev; A. Van Hoorn; in Software Engineering 2024 (2024).
  • Comprehensive Exploration of Synthetic Data Generation: A Survey. A. Bauer; S. and Trapp; M. and Stenger; R. and Leppich; S. and Kounev; M. and Leznik; K. and Chard; I. and Foster; in arXiv preprint (2024). 103.
    https://doi.org/10.48550/arXiv.2401.02524
  • Early Explorations of Lig...
    Early Explorations of Lightweight Models for Wound Segmentation on Mobile Devices. V. Borst; T. Dittus; K. Müller; S. Kounev; in 47th German Conference on Artificial Intelligence - KI 2024 (2024).
    just accepted
  • Security Analysis of a Decentralized, Revocable and Verifiable Attribute-Based Encryption Scheme. T. Prantl; M. Lauer; L. Horn; S. Engel; D. Dingel; S. Kounev; A. Bauer; C. Krupitzer; in Proceedings of the 19th International Conference on Availability, Reliability and Security (2024).
  • Unveiling Temporal Perfor...
    Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis. A. Bauer; T. Dittus; M. Straesser; A. Kamatar; M. Baughman; L. Beierlieb; M. Hadry; D. Grillmeyer; Y. Lubas; S. Kounev; I. Foster; K. Chard; in Companion of the 15th ACM/SPEC International Conference on Performance Engineering (2024). 72–76.
  • Benchmarking of Secure Group Communication schemes with Focus on IoT. T. Prantl; A. Bauer; S. Engel; L. Horn; C. Krupitzer; L. Iffl"ander; S. Kounev; in Discover Data (2024). 2(1)
2023[ to top ]
  • Recommendation of Secure Group Communication Schemes using Multi Objective Optimization. T. Prantl; A. Bauer; L. Iffländer; C. Krupitzer; S. Kounev; in International Journal of Information Security (2023).
  • An Empirical Study of Con...
    An Empirical Study of Container Image Configurations and Their Impact on Start Times. M. Straesser; A. Bauer; R. Leppich; N. Herbst; K. Chard; I. Foster; S. Kounev; in 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (2023). 94–105.
  • Autoscaler Evaluation and...
    Autoscaler Evaluation and Configuration: A Practitioner’s Guideline. M. Straesser; S. Eismann; J. von Kistowski; A. Bauer; S. Kounev; in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 31–41.
  • ExDe: Design space exploration of scheduler architectures and mechanisms for serverless data-processing. S. Talluri; N. Herbst; C. Abad; T. De Matteis; A. Iosup; in Future Generation Computer Systems (2023).
    https://www.sciencedirect.com/science/article/pii/S0167739X23004211
  • Performance Impact Analysis of Homomorphic Encryption: A Case Study Using Linear Regression as an Example. T. Prantl; S. Engel; L. Horn; D. Kaiser; L. Iffländer; A. Bauer; C. Krupitzer; S. Kounev; in Information Security Practice and Experience, W. Meng, Z. Yan, V. Piuri (Hrsg.) (2023). 284–298.
  • Deep Neural Network Regression for Normalized Digital Surface Model Generation with Sentinel-2 Imagery. K. Müller; R. Leppich; C. Geiß; V. Borst; P. A. Pelizari; S. Kounev; in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023). 1–14.
  • Searching for the Ground ...
    Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. A. Bauer; M. Straesser; M. Leznik; L. Beierlieb; M. Hadry; N. Hudson; K. Chard; S. Kounev; I. Foster; in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 95–99.
  • Challenges and Future Directions in Efficiency Benchmarking (Vision Paper). M. Meissner; K.-D. Lange; S. Sharma; J. Arnold; A. Cragin; P. Galizia; M. Petrich; B. Zhang; S. Kounev; in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 51–55.
  • Kubernetes-in-the-Loop: E...
    Kubernetes-in-the-Loop: Enriching Microservice Simulation Through Authentic Container Orchestration. M. Straesser; P. Haas; S. Frank; A. Hakamian; A. Van Hoorn; S. Kounev; in Performance Evaluation Methodologies and Tools (2023).
    In print.
  • Power to the Applications...
    Power to the Applications: The Vision of Continuous Decentralized Autoscaling. M. Straesser; S. Geißler; T. Hoßfeld; S. Kounev; in 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW) (2023). 281–283.
  • Towards a Cryptography Encyclopedia: A Survey on Attribute-Based Encryption. T. Prantl; T. Zeck; L. Horn; L. Iffländer; A. Bauer; A. Dmitrienko; C. Krupitzer; S. Kounev; in Journal of Surveillance, Security and Safety (2023).
  • BLOCSIE - Benchmark for LOCalization in a Simulated Industrial Environment. F. Spiess; D. Bluemm; N. Strobel; T. Kaupp; S. Kounev; in 2023 21st International Conference on Advanced Robotics (ICAR) (2023). 577–584.
  • Performance Engineering o...
    Performance Engineering of Serverless Applications and Platforms. S. Eismann; Thesis; Universität Würzburg. (2023).
  • A literature review of Io...
    A literature review of IoT and CPS—What they are, and what they are not. V. Lesch; M. Züfle; A. Bauer; L. Iffländer; C. Krupitzer; S. Kounev; in Journal of Systems and Software (2023). 111631.
  • Segmentierung und Verlauf...
    Segmentierung und Verlaufskontrolle chronischer Wunden durch künstliche Intelligenz mithilfe einer mobilen App (WUNDERKINT Studie). V. Borst; T. Dege; F. Grän; S. Hamrouni; D. Michel; V. Hager; M. Goebeler; R. Leppich; S. Kounev; A. Schmieder; in Allergologie. JDDG: Journal der Deutschen Dermatologischen Gesellschaft (2023). (Bd. 21) 28–177.
    Poster Abstract (No. P322, pp. 175-176)
  • A Systematic Approach for...
    A Systematic Approach for Benchmarking of Container Orchestration Frameworks. M. Straesser; J. Mathiasch; A. Bauer; S. Kounev; in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 187–198.
  • De Bello Homomorphico: Investigation of the extensibility of the OpenFHE library with basic mathematical functions by means of common approaches using the example of the CKKS cryptosystem. T. Prantl; L. Horn; S. Engel; L. Iffländer; L. Beierlieb; C. Krupitzer; A. Bauer; M. Sakarvadia; I. Foster; S. Kounev; in International Journal of Information Security (2023).
  • Challenges in the development of the EO Exploitation Platform terrabyte. J. Eberle; M. Schwinger; J. Zeidler; in Big Data from Space, P. Soille, S. Lumnitz, S. Albani (Hrsg.) (2023). 97–100.
  • Self-Aware Optimization of Adaptation Planning Strategies. V. Lesch; M. Hadry; C. Krupitzer; S. Kounev; in ACM Transactions on Autonomous and Adaptive Systems (2023). 18(3)
  • Serverless Computing: Wha...
    Serverless Computing: What It Is, and What It Is Not?. S. Kounev; N. Herbst; C. L. Abad; A. Iosup; I. Foster; P. Shenoy; O. Rana; A. A. Chien; in Commun. ACM (2023). 66(9) 80–92.
  • MVNOCoreSim: A Digital Twin for Virtualized IoT-centric Mobile Core Networks. S. Geissler; F. Wamser; W. Bauer; S. Gebert; S. Kounev; T. Hossfeld; in IEEE Internet of Things (2023). 10(15) 13974–13987.
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, Issue 12. S. Kounev; A. van Hoorn; M. Straesser; A. Bauer; (2023, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • Optimizing storage assign...
    Optimizing storage assignment, order picking, and their interaction in mezzanine warehouses. V. Lesch; P. B. Müller; M. Krämer; M. Hadry; S. Kounev; C. Krupitzer; in Applied intelligence (2023). 25.
  • A Trace-driven Performanc...
    A Trace-driven Performance Evaluation of Hash-based Task Placement Algorithms for Cache-enabled Serverless Computing. S. Talluri; N. Herbst; C. Abad; A. Trivedi; A. Iosup; in 2023 ACM International Conference on Computing Frontiers (CF ’23) (2023).
  • Association between Postoperative Atrial Fibrillation Recurrences and Interatrial Block by the Time of Open-Heart Surgery. S. Leiler; J. Kalisnik; R. Bernik; A. Bauer; V. Günzler; P. Sluet; S. Kounev; T. Fischlein; in The Thoracic and Cardiovascular Surgeon (2023). 71(S 01) DGTHG-V130.
  • Telescope: An Automated H...
    Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. A. Bauer; M. Leznik; M. Stenger; R. Leppich; N. Herbst; S. Kounev; I. Foster; (2023).
2022[ to top ]
  • ICPE ’22: ACM/SPEC International Conference on Performance Engineering, Bejing, China, April 9 - 13, 2022, Companion Volume D. Feng; S. Becker; N. Herbst; P. Leitner; (D. Feng; S. Becker; N. Herbst; P. Leitner, Hrsg.) (2022). ACM.
  • Why Is It Not Solved Yet?...
    Why Is It Not Solved Yet? Challenges for Production-Ready Autoscaling. M. Straesser; J. Grohmann; J. von Kistowski; S. Eismann; A. Bauer; S. Kounev; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 105–115.
  • Investigating the Predictability of QoS Metrics in Cellular Networks. S. Herrnleben; J. Grohmann; V. Lesch; T. Prantl; F. Metzger; T. Hoßfeld; S. Kounev; in 2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS) (2022). 1–10.
  • Towards a Cryptography Benchmark: A View on Attribute Based Encryption Schemes. T. Prantl; T. Zeck; L. Iffländer; L. Beierlieb; A. Dmitrenko; C. Krupitzer; S. Kounev; in 2022 5th Conference on Cloud and Internet of Things (CIoT) (2022).
  • Retrospektive Analyse ausgewählter Belastungs-und Beanspruchungsparameter einer professionellen Fußball-mannschaft vor und während coronabedingter Kontakt-beschränkungen in der Spielsaison 2019/20. P. Kunz; P. Düking; R. Leppich; J. Lachmann; B. Sperlich; in Leipziger Sportwissenschaftliche Beiträge Jahrgang 63 (2022 Heft 1 (2022). 75.
  • Same, Same, but Dissimila...
    Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity. M. Leznik; J. Grohmann; N. Kliche; A. Bauer; D. Seybold; S. Eismann; S. Kounev; J. Domaschka; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 89–96.
  • Ransomware Detection in Databases through Dynamic Analysis of Query Sequences. C. Sendner; L. Iffländer; S. Schindler; M. Jobst; A. Dmitrienko; S. Kounev; in 2022 IEEE Conference on Communications and Network Security (CNS) (2022).
  • Artificial Intelligence-Based Early Detection Of Acute Kidney Injury After Cardiac Surgery. J. M. Kalisnik; A. Bauer; F. A. Vogt; F. J. Stickl; J. Zibert; M. Fittkau; T. Bertsch; S. Kounev; T. Fischlein; in European Journal of Cardio-Thoracic Surgery (2022).
    Joint first authorship; To be published soon
  • The State of Serverless A...
    The State of Serverless Applications: Collection, Characterization, and Community Consensus. S. Eismann; J. Scheuner; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; in Transactions on Software Engineering (2022). 48(10) 4152–4166.
  • ICPE ’22: ACM/SPEC International Conference on Performance Engineering, Bejing, China, April 9 - 13, 2022 D. Feng; S. Becker; N. Herbst; P. Leitner; (D. Feng; S. Becker; N. Herbst; P. Leitner, Hrsg.) (2022). ACM.
  • A data-driven Sensor Model for LIDAR Range Measurements used for Mobile Robot Navigation. F. Spiess; N. Strobel; T. Kaupp; S. Kounev; in Proceedings of the IEEE IRC 2022 Conference (2022).
  • Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial. P. Helmer; S. Hottenrott; P. Rodemers; R. Leppich; M. Helwich; R. Pryss; P. Kranke; P. Meybohm; B. E. Winkler; M. Sammeth; in Journal of Medical Internet Research (2022). 24(12) e42359.
  • MiSim: A Simulator for Resilience Assessment of Microservice-based Architectures. S. Frank; L. Wagner; A. Hakamian; M. Straesser; A. van Hoorn; in 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) (2022). 1014–1025.
  • Retrospective Analysis of Training Intensity Distribution Based on Race Pace Versus Physiological Benchmarks in Highly Trained Sprint Kayakers. M. Matzka; R. Leppich; B. Sperlich; C. Zinner; in Sports Medicine-Open (2022). 8(1) 1–12.
  • Proactive Critical Event ...
    Proactive Critical Event Prediction based on Monitoring Data with Focus on Technical Systems. M. O. Züfle; Thesis; Universität Würzburg. (2022).
  • CortexVR: Immersive analy...
    CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning. C. Krupitzer; J. Naber; J.-P. Stauffert; J. Mayer; J. Spielmann; P. Ehmann; N. Boci; M. Bürkle; A. Ho; C. Komorek; F. Heinickel; S. Kounev; C. Becker; M. E. Latoschik; in Frontiers in Psychology (2022). 5139.
  • A Survey on Secure Group Communication Schemes with Focus on IoT Communication. T. Prantl; T. Zeck; A. Bauer; P. Ten; D. Prantl; A. E. Ben Yahya; L. Iffländer; A. Dmitrienko; C. Krupitzer; S. Kounev; in IEEE Access (2022).
    Accepted but not yet published
  • Edge Workload Trace Gathering and Analysis for Benchmarking. K. Toczé; N. Schmitt; U. Kargén; A. Aral; I. Brandi’c; in 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC) (2022). 34–41.
  • SPEC Research - Introducing the Predictive Data Analytics Working Group. A. Bauer; M. Leznik; D. Seybold; I. Trubin; B. Erb; J. Domaschka; P. Jamshidi; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • Identification of clinically distinct and prognostically important phenogroups in patients with acute heart failure by a machine learning approach. J. J. Albert; R. Leppich; V. Borst; F. Sahiti; N. Scholz; V. Cejka; C. Morbach; G. Ertl; C. Angermann; S. Frantz; others; in EUROPEAN JOURNAL OF HEART FAILURE (2022). (Bd. 24) 179–179.
  • Automated Triage of Perfo...
    Automated Triage of Performance Change Points Using Time Series Analysis and Machine Learning. A. Bauer; M. Straesser; L. Beierlieb; M. Meissner; S. Kounev; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, Issue 11. S. Kounev; A. van Hoorn; M. Straesser; A. Bauer; (2022, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • FADE: Towards Flexible an...
    FADE: Towards Flexible and Adaptive Distance Estimation Considering Obstacles. M. Hadry; V. Lesch; S. Kounev; in Companion of the 13th ACM/SPEC International Conference on Performance Engineering (ICPE 2022) (2022).
  • SPEC Research - Introduci...
    SPEC Research - Introducing the Predictive Data Analytics Working Group. A. Bauer; M. Leznik; D. Seybold; I. Trubin; B. Erb; J. Domaschka; P. Jamshidi; in Companion of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • Change Point Detection for MongoDB Time Series Performance Regression. M. Leznik; M. S. Iqbal; I. A. Trubin; A. Lochner; P. Jamshidi; A. Bauer; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • Self-Aware Optimization of Cyber-Physical Systems in Intelligent Transportation and Logistics Systems. V. Lesch; Thesis; Universität Würzburg. (2022, April).
  • Measurement, Modeling, and Emulation of Power Consumption of Distributed Systems. N. Schmitt; (2022, Juni).
  • SPEC Efficiency Benchmark...
    SPEC Efficiency Benchmark Development: How to Contribute to the Future of Energy Conservation. M. Meissner; K.-D. Lange; J. Arnold; S. Sharma; R. Tipley; N. Rawtani; D. Reiner; M. Petrich; A. Cragin; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • Model Learning for Perfor...
    Model Learning for Performance Prediction of Cloud-native Microservice Applications. J. Grohmann; Thesis; Universität Würzburg. (2022, März).
    Distinction
  • An Experience Report on the Suitability of a Distributed Group Encryption Scheme for an IoT Use Case. T. Prantl; S. Engel; A. Bauer; A. E. Ben Yahya; S. Herrnleben; L. Iffländer; A. Dmitrienko; S. Kounev; in 2022 IEEE 95th Vehicular Technology Conference (VTC2022) (2022).
  • A literature review on op...
    A literature review on optimization techniques for adaptation planning in adaptive systems: State of the art and research directions. E. Henrichs; V. Lesch; M. Straesser; S. Kounev; C. Krupitzer; in Information and Software Technology (2022). 149 106940.
  • Towards Forecasting Future Snow Cover Dynamics in the European Alps - The Potential of Long Optical Remote-Sensing Time Series. J. Koehler; A. Bauer; A. J. Dietz; C. Kuenzer; in Remote Sensing (2022). 14(18)
  • A case study on the stabi...
    A case study on the stability of performance tests for serverless applications. S. Eismann; D. Costa; L. Liao; C.-P. Bezemer; W. Shang; A. van Hoorn; S. Kounev; in Journal of Systems and Software (JSS) (2022). 189
  • Experience and Guidelines for Sorting Algorithm Choices and Their Energy Efficiency. M. Meissner; S. Kamthania; N. Rawtani; J. Bucek; K.-D. Lange; S. Kounev; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • The Relationship Between the Distribution of Training Intensity and Performance of Kayak and Canoe Sprinters: A Retrospective Observational Analysis of One Season of Competition. M. Matzka; R. Leppich; H.-C. Holmberg; B. Sperlich; C. Zinner; in Frontiers in Sports and Active Living (2022). 3 788108.
2021[ to top ]
  • 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 Research Challenges in Information Science (RCIS) (2021). 189–204.
  • An Overview on Approaches...
    An Overview on Approaches for Coordination of Platoons. V. Lesch; M. Breitbach; M. Segata; C. Becker; S. Kounev; C. Krupitzer; in IEEE Transactions on Intelligent Transportation Systems (2021).
    Early Access on IEEE Xplore
  • ComBench: A Benchmarking...
    ComBench: A Benchmarking Framework for Publish/Subscribe Communication Protocols Under Network Limitations. S. Herrnleben; M. Leidinger; V. Lesch; T. Prantl; J. Grohmann; C. Krupitzer; S. Kounev; in Performance Evaluation Methodologies and Tools, Q. Zhao, L. Xia (Hrsg.) (2021). 72–92.
  • 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: The Journal of Automation (2021).
    (in press)
  • Towards Situation-Aware M...
    Towards Situation-Aware Meta-Optimization of Adaptation Planning Strategies. V. Lesch; T. Noack; J. Hefter; S. Kounev; C. Krupitzer; in Proceedings of the 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems - ACSOS 2021 (2021).
    Best Paper Award Runner Up, Full Paper Acceptance Ratio: 25%
  • Tackling the Rich Vehicle Routing Problem with Nature-Inspired Algorithms. V. Lesch; M. König; S. Kounev; A. Stein; C. Krupitzer; in Applied Intelligence (2021). 52 9476–9500.
  • A Case Study on Optimizat...
    A Case Study on Optimization of Platooning Coordination V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; (2021).
  • The integration of training and off-training activities substantially alters training volume and load analysis in elite rowers. G. Treff; R. Leppich; K. Winkert; J. M. Steinacker; B. Mayer; B. Sperlich; in Scientific reports (2021). 11(1) 1–10.
  • Teaching Software Testing Using Automated Grading. L. Beierlieb; L. Iffländer; T. Schneider; T. Prantl; S. Kounev; in Proceedings of the Fifth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2021),virtual event, October 28-29, 2021, A. Greubel, S. Strickroth, M. Striewe (Hrsg.) (2021).
  • Software Testing Strategies for Detecting Hypercall Handlerstextquotesingle Aging-related Bugs. L. Beierlieb; A. Avritzer; L. Ifflander; N. Antunes; A. Milenkoski; S. Kounev; in 2021 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (2021).
  • Benchmarking of Pre- and Post-Quantum Group Encryption Schemes with Focus on IoT. T. Prantl; D. Prantl; A. Bauer; L. Iffländer; A. Dmitrenko; C. Krupitzer; S. Kounev; in 2021 IEEE 40th International Performance Computing and Communications Conference (IPCCC) (2021).
  • 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.
  • Machine Learning Model Update Strategies for Hard Disk Drive Failure Prediction. M. Züfle; F. Erhard; S. Kounev; in 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2021).
    (to appear)
  • Automatisierte Hybride Zeitreihenprognose. A. Bauer; in Ausgezeichnete Informatikdissertationen 2020, S. Hölldobler (Hrsg.) (2021). 29–38.
  • Serverless Computing (Dagstuhl Seminar 21201). C. Abad; I. T. Foster; N. Herbst; A. Iosup; in Dagstuhl Reports, (C. Abad; I. T. Foster; N. Herbst; A. Iosup, Hrsg.) (2021). 11(4) 34–93.
  • A Case Study of Vehicle R...
    A Case Study of Vehicle Route Optimization V. Lesch; M. König; S. Kounev; A. Stein; C. Krupitzer; (2021).
  • A Case Study on Optimization of Warehouses. V. Lesch; P. Müller; M. Krämer; S. Kounev; C. Krupitzer; in arXiv preprint arXiv:2112.12058 (2021).
  • Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases. A. Bauer; Thesis; Universität Würzburg. (2021).
  • A Case Study on Optimizat...
    A Case Study on Optimization of Warehouses V. Lesch; P. B. Müller; M. Krämer; S. Kounev; C. Krupitzer; (2021).
  • 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).
  • Serverless Applications:W...
    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.
  • Buzzy: Towards Realistic ...
    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.
  • Performance Evaluation of a Post-Quantum Public-Key Cryptosystem. T. Prantl; D. Prantl; L. Beierlieb; L. Iffländer; A. Dmitrienko; C. Krupitzer; S. Kounev; in 2021 IEEE 40th International Performance Computing and Communications Conference (IPCCC) (2021).
  • Towards Scientific and Interoperable Earth Observation Exploitation Platforms. J. Eberle; M. Schwinger; H. Zwenzner; in Proceedings of the 2021 conference on Big Data from Space, P. Soille, S. Loekken, M. Albani (Hrsg.) (2021). 89–92.
  • People Detection with Depth Silhouettes and Convolutional Neural Networks on a Mobile Robot. F. Spiess; L. Reinhart; N. Strobel; D. Kaiser; S. Kounev; T. Kaupp; in Journal of Image and Graphics, (J. of Image; Graphics, Hrsg.) (2021). 9(4) 135–139.
  • Sizeless: Predicting the ...
    Sizeless: Predicting the Optimal Size of Serverless Functions. S. Eismann; L. Bui; J. Grohmann; C. Abad; N. Herbst; S. Kounev; in Proceedings of the 22nd International MIDDLEWARE Conference (2021). 248–259.
    Best Student Paper Award, ACM Artifacts Evaluated — Functional
  • Energy-Efficiency Comparison of Common Sorting Algorithms. N. Schmitt; S. Kamthania; N. Rawtani; L. Mendoza; K.-D. Lange; S. Kounev; in 2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2021). 1–8.
  • Towards Splitting Monolithic Workflows into Serverless Functions and Estimating Their Run-Time in the Earth Observation Domain. D. Kaiser; B. Dovhan; A. Bauer; S. Kounev; in Proceedings of the 12th Symposium on Software Performance (SSP) (2021).
    Extended Abstract
  • Measuring the Performance Impact of Branching Instructions. L. Beierlieb; L. Iffländer; A. Milenkoski; T. Prantl; S. Kounev; in Proceedings of the 12th Symposium on Software Performance 2021 (SSP’21) (2021).
  • A Simulation-based Optimi...
    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.
  • A Predictive Maintenance ...
    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).
  • SARDE: A Framework for Co...
    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)
  • Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment. F. Spiess; J. Friesslich; D. Bluemm; F. Mast; D. Vinokour; S. Kounev; T. Kaupp; N. Strobel; in 2021 20th International Conference on Advanced Robotics (ICAR) (2021). 857–864.
  • Scalable Processing Of Copernicus Sentinel satellite Images Using Argo Workflows. F. W. Fichtner; N. Mandery; M. Schwinger; J. Eberle; M. Nolde; T. Riedlinger; in Big Data from Space 2021 (2021). 77–80.
  • SuanMing: Explainable Pre...
    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%
  • SPEC - Spotlight on the International Standards Group (ISG). N. Schmitt; K.-D. Lange; S. Sharma; A. Cragin; D. Reiner; S. Kounev; in Companion of the ACM/SPEC International Conference on Performance Engineering (2021).
  • A Comparison of Mechanism...
    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.
  • Utility-based Vehicle Rou...
    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).
  • Attack-aware Security Fun...
    Attack-aware Security Function Management. L. Iffländer; Thesis; Universität Würzburg. (2021, Januar).
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, vol. 3 no. 2. S. Kounev; A. van Hoorn; A. Bauer; (2021, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • Libra: A Benchmark for Ti...
    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).
2020[ to top ]
  • REACT: A Model-Based Runt...
    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).
  • 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).
  • 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, Februar).
  • Towards Self-Aware Multir...
    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
  • 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.
  • Introduction to the Speci...
    Introduction to the Special Issue ``Applications in Self-Aware Computing Systems and their Evaluation’’. C. Krupitzer; B. Eberhardinger; I. Gerostathopoulos; C. Raibulet; (2020).
  • Beyond Microbenchmarks: T...
    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).
  • Systems Benchmarking S. Kounev; K.-D. Lange; J. von Kistowski; (2020). (1. Aufl.) Springer International Publishing.
  • 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.
  • 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.
  • An Overview of Design Pat...
    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).
  • 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.
  • Learning to Learn in Coll...
    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.
  • SIMPL: Secure IoT Managem...
    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).
  • Toward a Framework for Self-Learning Adaptation Planning through Optimization. V. Lesch; in Organic Computing: Doctoral Dissertation Colloquium 2020 (2020).
  • Methodological Principles...
    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.
  • A Survey on Predictive Ma...
    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).
  • A Survey on Human Machine...
    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).
  • Quantifying measurement q...
    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).
  • To Fail Or Not To Fail: P...
    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.
  • 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.
  • Incremental Calibration o...
    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.
  • Performance, Power, and Energy-Efficiency Impact Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite. N. Schmitt; J. Bucek; J. Beckett; A. Cragin; K.-D. Lange; S. Kounev; in 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC) (2020). 292–301.
  • 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%
  • Baloo: Measuring and Mode...
    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%
  • A Framework for Time Seri...
    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).
  • Optimizing Parametric Dep...
    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.