Publications

I have been working on resource management and scheduling, scalable and fault-tolerant distributed systems, distributed data processing and data-intensive applications, as well as software development tools.

Full list of my papers and theses:

papers:
  • AuctionWhisk: Using an Auction-Inspired Approach for Function Placement in Serverless Fog Platforms. David Bermbach, Jonathan Bader, Jonathan Hasenburg, Tobias Pfandzelter, and Lauritz Thamsen. To appear in Software: Practice and Experience. Wiley. 2021. [pdf]
    • Open access also via the Wiley Online Library, once published.
  • On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds. Dominik Scheinert, Alireza Alamgiralem, Jonathan Bader, Jonathan Will, Thorsten Wittkopp, and Lauritz Thamsen. To appear in the Proceedings of the 2021 IEEE International Conference on Big Data (Big Data). To be presented at the 5th International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD). IEEE. 2021. [pdf]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. Jonathan Will, Onur Arslan, Jonathan Bader, Dominik Scheinert, and Lauritz Thamsen. To appear in the Proceedings of the 2021 IEEE International Conference on Big Data (Big Data). To be presented at the 5th International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD). IEEE. 2021. [pdf]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters. Jonathan Bader, Lauritz Thamsen, Svetlana Kulagina, Jonathan Will, Henning Meyerhenke, and Odej Kao. To appear in the Proceedings of the 2021 IEEE International Conference on Big Data (Big Data). IEEE. 2021. [pdf] [code]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kordian Gontarska, and Lauritz Thamsen. To appear in the Proceedings of the 22nd ACM/IFIP International Middleware Conference (Middleware). ACM. 2021. [pdf] [code]
    • © ACM, 2021. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in the Middleware'21 Proceedings.
  • Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation. Dominik Scheinert, Houkun Zhu, Lauritz Thamsen, Morgan K. Geldenhuys, Jonathan Will, Alexander Acker, and Odej Kao. To appear in the Proceedings of the 40th IEEE International Performance Computing and Communications Conference (IPCCC). IEEE. 2021. [pdf] [code]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • On the Future of Cloud Engineering. David Bermbach, Abhishek Chandra, Chandra Krintz, Aniruddha Gokhale, Aleksander Slominski, Lauritz Thamsen, Everton Cavalcante, Tian Guo, Ivona Brandic, and Rich Wolski. To appear in the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). IEEE. 2021. [pdf]
    • https://doi.org/10.1109/IC2E52221.2021.00044, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Assessing the Resilience of Water Distribution Networks Under Different Sensor Network Architectures and Data Sampling Frequencies. Siling Chen, Florian Brokhausen, Philipp Wiesner, Lauritz Thamsen, and Andrea Cominola. In the Proceedings of the 2nd International Symposium on Water System Operations (ISWSO). IAHR. 2021. [pdf]
  • GRAL: Localization of Floating Wireless Sensors in Pipe Networks. Martin Haug, Felix Lorenz, and Lauritz Thamsen. To appear in the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). To be presented at the First International Workshop on Testing Distributed Internet of Things Systems (TDIS). IEEE. 2021. [pdf] [code]
    • https://doi.org/10.1109/IC2E52221.2021.00042, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures. Morgan Geldenhuys, Jonathan Will, Benjamin Pfister, Martin Haug, Alex Scharmann, and Lauritz Thamsen. To appear in the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). To be presented at the First International Workshop on Testing Distributed Internet of Things Systems (TDIS). IEEE. 2021. [pdf] [code]
    • https://doi.org/10.1109/IC2E52221.2021.00041, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. Dominik Scheinert, Lauritz Thamsen, Houkun Zhu, Jonathan Will, Alexander Acker, Thorsten Wittkopp, and Odej Kao. In the Proceedings of the 23rd IEEE International Conference on Cluster Computing (CLUSTER). IEEE. 2021. [pdf] [code]
    • https://doi.org/10.1109/Cluster48925.2021.00052, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks. Soeren Becker, Florian Schmidt, Lauritz Thamsen, Ana Juan Ferrer, and Odej Kao. To appear in the Proceedings of the 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS). IEEE. 2021. [pdf]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Rafiki: Task-level Capacity Planning in Distributed Stream Processing Systems. Benjamin J. J. Pfister, Wolf S. Lickefett, Jan Nitschke, Sumit Paul, Morgan K. Geldenhuys, Dominik Scheinert, Kordian Gontarska, and Lauritz Thamsen. To appear in the Proceedings of the Euro-Par 2021 Workshops (Euro-Par). Presented at the 3rd International Workshop on Parallel Programming Models in High-Performance Cloud (ParaMo). Springer. 2021. [pdf] [code]
    • © Springer, 2021. The final authenticated version will be available online later via Springer Link.
  • C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Jonathan Bader, and Odej Kao. To appear in the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). IEEE. 2021. [pdf] [code]
    • https://doi.org/10.1109/IC2E52221.2021.00018, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Evaluation of Load Prediction Techniques for Distributed Stream Processing. Kordian Gontarska, Morgan Geldenhuys, Dominik Scheinert, Philipp Wiesner, Andreas Polze, and Lauritz Thamsen. To appear in the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). IEEE. 2021. [pdf]
    • https://doi.org/10.1109/IC2E52221.2021.00023, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems. Robert Danicki, Martin Haug, Ilja Behnke, Laurenz Mädje, and Lauritz Thamsen. In the Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys), co-located with the 16th European Conference on Computer Systems (EuroSys). ACM. 2021. [pdf]
    • © ACM, 2021. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the EdgeSys'21 Proceedings.
  • Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. Kordian Gontarska, Weronika Wrazen, Jossekin Beilharz, Robert Schmid, Lauritz Thamsen, and Andreas Polze. Lecture Notes in Artificial Intelligence (LNAI). Presented at the 19th Conference on Artificial Intelligence in Medicine (AIME). Springer. 2021. [pdf]
  • Control Optimization Through Prediction-Based Wastewater Management. David Konstantin Tilcher, Florin Popescu, Harald Sommer, Lauritz Thamsen, and Paul Uwe Thamsen. In the 2021 ASME Conference Proceedings. Presented at the 2021 ASME Fluids Engineering Division Summer Meeting (FEDSM). ASME. 2021.
  • LEAF: Simulating Large Energy-Aware Fog Computing Environments. Philipp Wiesner and Lauritz Thamsen. In the Proceedings of the 5th IEEE International Conference on Fog and Edge Computing (ICFEC). IEEE. 2021. [pdf] [code]
    • https://doi.org/10.1109/ICFEC51620.2021.00012, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms. Ana Juan Ferrer, Sören Becker, Florian Schmidt, Lauritz Thamsen, and Odej Kao. To appear in the Workshop Proceedings of the 21st IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid Workshops). Presented at the 1st Workshop on the Cloud-to-Things Continuum (Cloud2Things). IEEE. 2021. [pdf]
    • To be published by IEEE. © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies. Dominik Scheinert, Alexander Acker, Lauritz Thamsen, Morgan K. Geldenhuys, and Odej Kao. In the Workshop Proceedings of the 43th International Conference on Software Engineering (ICSE Workshops). Presented at the 2nd Workshop on Cloud Intelligence (CloudIntelligence). IEEE. 2021. [pdf]
    • © ACM, 2021. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the ICSE Workshops Proceedings.
  • PIERES: A Playground for Network Interrupt Experiments on Real-Time Embedded Systems in the IoT. Franz Bender, Jan Jonas Brune, Nick Lauritz Keutel, Ilja Behnke and Lauritz Thamsen. In the Companion of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE Companion). Presented at the 9th International Workshop on Load Testing and Benchmarking of Software Systems (LTB). ACM. 2021. [pdf]
    • https://doi.org/10.1145/3447545.3451189, © ACM, 2021. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the ICPE Companion.
  • Towards a Staging Environment for the Internet of Things. Jossekin Beilharz, Philipp Wiesner, Arne Boockmeyer, Florian Brokhausen, Ilja Behnke, Robert Schmid, Lukas Pirl, and Lauritz Thamsen. In the Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). Presented in the Work in Progress (WiP) session of the conference. IEEE. 2021. Best WiP Paper. [pdf] [code]
    • https://doi.org/10.1109/PerComWorkshops51409.2021.9431087, © IEEE 2021. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs. Morgan K. Geldenhuys, Lauritz Thamsen, and Odej Kao. In the Proceedings of the 2020 IEEE International Conference on Big Data (Big Data). IEEE. 2020. [pdf]
    • https://doi.org/10.1109/BigData50022.2020.9378474, © IEEE 2020. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring. Felix Lorenz, Morgan Geldenhuys, Harald Sommer, Frauke Jakobs, Carsten Lüring, Volker Skwarek, Ilja Behnke, and Lauritz Thamsen. In the Proceedings of the 2020 IEEE International Conference on Big Data (Big Data). Presented at the Second International Workshop on the Internet of Things Data Analytics (IoTDA). IEEE. 2020. [pdf] [code]
    • https://doi.org/10.1109/BigData50022.2020.9378138, © IEEE 2020. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs. Jonathan Will, Jonathan Bader, and Lauritz Thamsen. In the Proceedings of the 2020 IEEE International Conference on Big Data (Big Data). Presented at the 4th International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD). IEEE. 2020. [pdf] [video] [data]
    • https://doi.org/10.1109/BigData50022.2020.9377994, © IEEE 2020. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet?. Ilja Behnke, Lukas Pirl, Lauritz Thamsen, Robert Danicki, Andreas Polze, and Odej Kao. In the Proceedings of the 39th IEEE International Performance Computing and Communications Conference (IPCCC). IEEE. 2020. [pdf] [video]
    • https://doi.org/10.1109/IPCCC50635.2020.9391536, © IEEE 2020. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Mary, Hugo, and Hugo*: Learning to Schedule Distributed Data-Parallel Processing Jobs on Shared Clusters. Lauritz Thamsen, Jossekin Beilharz, Vinh Thuy Tran, Sasho Nedelkoski, and Odej Kao. In Concurrency and Computation: Practice and Experience (e5823). Wiley. 2020. [pdf] [code]
  • Fingerprinting Analog IoT Sensors for Secret-Free Authentication. Felix Lorenz, Lauritz Thamsen, Andreas Wilke, Ilja Behnke, Jens Waldmüller-Littke, Ilya Komarov, Odej Kao, and Manfred Paeschke. In the Workshop Proceedings of the 29th International Conference on Computer Communications and Networks (ICCCN). Presented at the 10th International Workshop on Security, Privacy, Trust, and Machine Learning for Internet of Things (IoTSPT-ML). IEEE. 2020. [pdf]
    • https://doi.org/10.1109/ICCCN49398.2020.9209643, © IEEE 2020. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Effectively Testing System Configurations of Critical IoT Analytics Pipelines. Morgan K. Geldenhuys, Lauritz Thamsen, Kain Kordian Gontarska, Felix Lorenz, and Odej Kao. In the Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData). Presented at the Second International Workshop on the Internet of Things Data Analytics (IoTDA). IEEE. 2019. [pdf]
    • https://doi.org/BigData47090.2019.9005504, © IEEE 2019. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Héctor: A Framework for Testing IoT Applications Across Heterogeneous Edge and Cloud Testbeds. Ilja Behnke, Lauritz Thamsen, and Odej Kao. In the Companion of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC Companion). Presented at the 8th International Workshop on Cloud and Edge Computing and Applications Management (CloudAM). ACM. 2019. [pdf] [code]
    • © ACM, 2019. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the UCC Companion.
  • Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs. Lauritz Thamsen, Ilya Verbitskiy, Sasho Nedelkoski, Vinh Thuy Tran, Vinícius Meyer, Miguel G. Xavier, Odej Kao, and César A. F. De Rose. In the Proceedings of the Euro-Par 2019 Workshops (Euro-Par). Presented at the 1st International Workshop on Parallel Programming Models in High-Performance Cloud. Springer (ParaMo). 2019. [pdf] [code]
  • Multilayer Active Learning for Efficient Learning and Resource Usage in Distributed IoT Architectures. Sasho Nedelkoski, Lauritz Thamsen, Ilya Verbitskiy, and Odej Kao. In the Proceedings of the 2019 IEEE International Conference on Edge Computing (EDGE). IEEE. 2019. [pdf]
    • https://doi.org/10.1109/EDGE.2019.00015, © IEEE 2019. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • CoBell: Runtime Prediction for Distributed Dataflow Jobs in Shared Clusters. Ilya Verbitskiy, Lauritz Thamsen, Thomas Renner, and Odej Kao. In the Proceedings of the 10th IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE. 2018. [pdf]
    • https://doi.org/10.1109/CloudCom2018.2018.00029, © IEEE 2018. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Scheduling Stream Processing Tasks on Geo-Distributed Heterogeneous Resources. Gerrit Janßen, Ilya Verbitskiy, Thomas Renner, and Lauritz Thamsen. In the Proceedings of the 2018 IEEE International Conference on Big Data (IEEE BigData). Presented at the First International Workshop on the Internet of Things Data Analytics (IoTDA). IEEE. 2018. [pdf]
    • https://doi.org/10.1109/BigData.2018.8622651, © IEEE 2018. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Learning Efficient Co-locations for Scheduling Distributed Dataflows in Shared Clusters. Lauritz Thamsen, Ilya Verbitskiy, Benjamin Rabier, and Odej Kao. In Services Transactions on Big Data (Vol. 4, No. 1). Services Society. 2018. [pdf] [code]
  • Adaptive Resource Management for Distributed Data Analytics. Lauritz Thamsen, Thomas Renner, Ilya Verbitskiy, and Odej Kao. In Lucio Grandinetti, Seyedeh Leili Mirtaheri, Reza Shahbazian, Thomas Sterling, Vladimir Voevodin (eds.), Advances in Parallel Computing – Big Data and HPC: Ecosystem and Convergence. IOS Press. 2018. [pdf]
  • Ellis: Dynamically Scaling Distributed Dataflows to Meet Runtime Targets. Lauritz Thamsen, Ilya Verbitskiy, Jossekin Beilharz, Thomas Renner, Andreas Polze, and Odej Kao. In the Proceedings of the 9th IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE. 2017. Best Paper Candidate. [pdf] [code]
    • https://doi.org/10.1109/CloudCom.2017.37, © IEEE 2017. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • SMiPE: Estimating the Progress of Recurring Iterative Distributed Dataflows. Jannis Koch, Lauritz Thamsen, Florian Schmidt, and Odej Kao. In the Proceedings of the 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT). IEEE. 2017. [pdf] [code]
    • https://doi.org/10.1109/PDCAT.2017.00034, © IEEE 2017. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Scheduling Recurring Distributed Dataflow Jobs Based on Resource Utilization and Interference. Lauritz Thamsen, Benjamin Rabier, Florian Schmidt, Thomas Renner, and Odej Kao. In the Proceedings of the 6th IEEE BigData Congress. IEEE. 2017. [pdf] [code]
    • https://doi.org/10.1109/BigDataCongress.2017.28, © IEEE 2017. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Adaptive Resource Management for Distributed Data Analytics Based on Container-level Cluster Monitoring. Thomas Renner, Lauritz Thamsen, and Odej Kao. In the Proceedings of the 6th International Conference on Data Science, Technology and Applications (DATA). SCITEPRESS. 2017. [pdf] [code]
    • © SCITEPRESS, 2017. This contribution was presented at DATA 17. This is the authors' version of the work.
  • Addressing Hadoop’s Small File Problem With an Appendable Archive File Format. Thomas Renner, Johannes Müller, Lauritz Thamsen, and Odej Kao. In the Proceedings of the Big Data Analytics Workshop (BigDAW), co-located with the ACM International Conference on Computing Frontiers. ACM. 2017. [pdf] [code]
    • © ACM, 2017. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the proceedings of the Big Data Analytics Workshop (BigDAW17).
  • Selecting Resources for Distributed Dataflow Systems According to Runtime Targets. Lauritz Thamsen, Ilya Verbitskiy, Florian Schmidt, Thomas Renner, and Odej Kao. In the Proceedings of the 35th IEEE International Performance Computing and Communications Conference (IPCCC). IEEE. 2016. [pdf] [code] [data]
    • https://doi.org/10.1109/PCCC.2016.7820629, © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • CoLoc: Distributed Data and Container Colocation for Data-Intensive Applications. Thomas Renner, Lauritz Thamsen, and Odej Kao. In the Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData). Presented at the 4th International Workshop on Distributed Storage Systems and Coding for Big Data. IEEE. 2016. [pdf]
    • https://doi.org/10.1109/BigData.2016.7840954, © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Visually Programming Dataflows for Distributed Data Analytics. Lauritz Thamsen, Thomas Renner, Marvin Byfeld, Markus Paeschke, Daniel Schröder, and Felix Böhm. In the Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData). Presented at the 3rd Workshop on Advances in Software and Hardware for Big Data to Knowledge Discovery (ASH). IEEE. 2016. [pdf] [code]
    • https://doi.org/10.1109/BigData.2016.7840860, © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • When to Use a Distributed Dataflow Engine: Evaluating the Performance of Apache Flink. Ilya Verbitskiy, Lauritz Thamsen, and Odej Kao. In the Proceedings of the IEEE International Conference on Cloud and Big Data Computing (CBDCom). IEEE. 2016. [pdf]
    • https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0114, © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Continuously Improving the Resource Utilization of Iterative Parallel Dataflows. Lauritz Thamsen, Thomas Renner, and Odej Kao. In the Proceedings of the IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW). Presented at the International Workshop on Big Data and Cloud Performance (DCPerf). IEEE. 2016. [pdf] [code]
    • http://dx.doi.org/10.1109/ICDCSW.2016.20, © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Aura: A Flexible Dataflow Engine for Scalable Data Processing. Tobias Herb, Lauritz Thamsen, Thomas Renner, and Odej Kao. In Andreas Knüpfer, Tobias Hilbrich, Christoph Niethammer, José Gracia, Wolfgang E. Nagel, Michael M. Resch (eds.), Tools for High Performance Computing 2015. Springer. 2016. [pdf] [code]
  • Exploratory Authoring of Interactive Content in a Live Environment. Philipp Otto, Jaqueline Pollak, Daniel Werner, Felix Wolff, Bastian Steinert, Lauritz Thamsen, Marcel Taeumel, Jens Lincke, Robert Krahn, Daniel H. H. Ingalls, and Robert Hirschfeld. HPI Technical Reports, vol. 101. Hasso Plattner Institute. 2016. [pdf]
  • Lively Groups: Shared Behavior in a World of Objects without Classes or Prototypes. Tim Felgentreff, Jens Lincke, Robert Hirschfeld, and Lauritz Thamsen. In the Proceedings of the Future Programming Workshop (FPW) 2015, co-located with the Conference on Object-oriented Programming, Systems, Languages, and Applications (OOPSLA). ACM. 2015. [pdf]
    • © ACM, 2015. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the proceedings of the Future Programming Workshop (FPW) 2015.
  • Network-Aware Resource Management for Scalable Data Analytics Frameworks. Thomas Renner, Lauritz Thamsen, and Odej Kao. In the Proceedings of the First Workshop on Data-Centric Infrastructure for Big Data Science (DIBS) 2015, co-located with the 2015 IEEE International Conference on BigData (BigData). IEEE. 2015. [pdf] [code]
    • http://dx.doi.org/10.1109/BigData.2015.7364083, © IEEE 2015. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
  • Preserving Access to Previous System States in the Lively Kernel. Lauritz Thamsen, Bastian Steinert, and Robert Hirschfeld. In Hasso Plattner, Christoph Meinel, and Larry Leifer (eds.), Design Thinking Research: Making Design Thinking Foundational. Springer. 2015. [pdf] [code]
  • Implicit Parallelism through Deep Language Embedding. Alexander Alexandrov, Andreas Kunft, Asterios Katsifodimos, Felix Schüler, Lauritz Thamsen, Odej Kao, Tobias Herb, and Volker Markl. In the Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD). ACM. 2015. [pdf] [project]
    • © ACM, 2015. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the proceedings of the ACM SIGMOD international conference.
  • Object Versioning to Support Recovery Needs: Using Proxies to Preserve Previous Development States in Lively. Bastian Steinert, Lauritz Thamsen, Tim Felgentreff, and Robert Hirschfeld. In the Proceedings of the Dynamic Languages Symposium (DLS) 2014, co-located with the Conference on Object-oriented Programming, Systems, Languages, and Applications (OOPSLA). ACM. 2014. [pdf] [code]
    • © ACM, 2014. This is the authors' version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is published in the proceedings of the Dynamic Languages Symposium.
  • Orca: A Single-language Web Framework for Collaborative Development. Lauritz Thamsen, Anton Gulenko, Michael Perscheid, Robert Krahn, Robert Hirschfeld, and David A. Thomas. In the Proceedings of the Conference on Creating, Connecting and Collaborating through Computing (C5) 2012. IEEE. 2012. [pdf] [project]
    • http://dx.doi.org/10.1109/C5.2012.9, © IEEE 2012. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
theses:
  • Dynamic Resource Allocation for Distributed Dataflows. Lauritz Thamsen. PhD thesis submitted at TU Berlin in March 2018 and successfully defended on May 4, 2018. [pdf] [slides]
  • Object Versioning for the Lively Kernel: Preserving Access to Previous System States in an Object-oriented Programming System. Lauritz Thamsen. Master thesis submitted at Hasso-Plattner-Institut, University of Potsdam, in May 2014. [pdf] [slides] [code]
  • Object Collaboration in the Orca Web Framework. Lauritz Thamsen. Bachelor thesis submitted at Hasso-Plattner-Institut, University of Potsdam, in June 2011. [pdf] [project]