Dr Lauritz Thamsen

  • Lecturer in Computer Systems (School of Computing Science)

telephone: 0141 330 2000 (x0652)
email: Lauritz.Thamsen@glasgow.ac.uk
pronouns: He/him/his

School of Computing Science, Sir Alwyn Williams Building, 18 Lilybank Gardens, University of Glasgow, Glasgow, G12 8RZ

Biography

I am a Lecturer in Computer Systems in the School of Computing Science at the University of Glasgow, focusing on resource-efficient and resilient distributed computer systems.

Within the School, I lead the Glasgow Carbon-Conscious Computing (GC3) lab, I am a member of the Glasgow Systems Section (GLASS), and I am part of the Glasgow Parallelism Group (GPG). I am furthermore involved in the School's Low-Carbon and Sustainable Computing and Trustworthy Autonomous Systems activities.

Beyond the School, I co-lead the collaboration on Adaptive Resource Management (ARM) with TU Berlin and started the Distributed Systems Engineering Lab (diselab), a collaboration with researchers from TU Berlin and Hasso Plattner Institute (HPI).

Before joining the University of Glasgow, I was a senior researcher in the Distributed and Operating Systems group at TU Berlin, lecturing on Cloud Computing and on Distributed Systems, and a guest professor in the Department of Computer Science at HU Berlin, substituting for Prof. Ulf Leser and lecturing on Data-Intensive Systems. At TU Berlin, I also completed a postdoc and did my PhD under Prof. Odej Kao, working on dynamic resource allocation for distributed dataflow systems. Prior to that, I was part of the Software Architecture Group of Prof. Robert Hirschfeld and the Research School at HPI, and I worked at SAP Labs in Palo Alto, California, in the Technology Infrastructure Practice group, under Dan Ingalls, as well as at Signavio in Berlin.

More about me and my research can be found at https://lauritzthamsen.org/.

Research interests

I am keen on making computing more accessible and sustainable. To this end, I work on methods and tools that make it easier to create resource-efficient and resilient distributed computer systems, focusing especially on carbon-aware computing and data-intensive applications in edge/cloud infrastructures.

My research interests include:

  • Distributed Computer Systems
  • Edge and Cloud Computing
  • Carbon-Aware Computing
  • Adaptive Resource Management
  • Data-Intensive Systems
  • Software Development and Operation Tools

Publications

Selected publications

Geldenhuys, M. K., Scheinert, D., Kao, O. and Thamsen, L. (2022) Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads. In: IEEE International Conference on Web Services (ICWS 2022), Barcelona, Spain, 11-15 July 2022, pp. 198-207. ISBN 9781665481434 (doi: 10.1109/ICWS55610.2022.00041)

Bader, J., Lehmann, F., Thamsen, L., Will, J., Leser, U. and Kao, O. (2022) Lotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters. In: 34th International Conference on Scientific and Statistical Database Management (SSDBM 2022), Copenhagen, Denmark, 6-8 July 2022, ISBN 9781450396677 (doi: 10.1145/3538712.3538739)

Wiesner, P., Behnke, I., Scheinert, D., Gontarska, K. and Thamsen, L. (2021) Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. In: 22nd International Middleware Conference (Middleware '21), 06-10 Dec 2021, pp. 260-272. ISBN 9781450385343 (doi: 10.1145/3464298.3493399)

Scheinert, D., Thamsen, L., Zhu, H., Will, J., Acker, A., Wittkopp, T. and Kao, O. (2021) Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. In: 2021 IEEE International Conference on Cluster Computing (CLUSTER), 07-10 Sep 2021, pp. 261-270. ISBN 9781728196664 (doi: 10.1109/Cluster48925.2021.00052)

Becker, S., Schmidt, F., Thamsen, L., Ferrer, A. J. and Kao, O. (2021) LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks. In: 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 27 Sep - 01 Oct 2021, pp. 41-50. ISBN 9781665412612 (doi: 10.1109/ACSOS52086.2021.00033)

All publications

List by: Type | Date

Jump to: 2023 | 2022 | 2021 | 2020 | 2018 | 2017 | 2016
Number of items: 51.

2023

Behnke, I., Blumschein, C., Danicki, R., Wiesner, P., Thamsen, L. and Kao, O. (2023) Towards a real-time IoT: approaches for incoming packet processing in cyber-physical systems. Journal of Systems Architecture, (doi: 10.1016/j.sysarc.2023.102891) (In Press)

Lehmann, F., Bader, J., Tschirpke, F., Thamsen, L. and Leser, U. (2023) How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow Scheduling Interface. In: 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023), Bangalore, India, 1-4 May 2023, (Accepted for Publication)

Scheinert, D., Becker, S., Bader, J., Thamsen, L., Will, J. and Kao, O. (2023) Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics. In: 2022 IEEE International Conference on Big Data, Osaka, Japan, 17-20 December 2022, pp. 209-216. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10020860)

Scheinert, D., Zadeh Aghdam, B. S., Becker, S., Kao, O. and Thamsen, L. (2023) Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments. In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), Osaka, Japan, 17-20 Dec 2022, pp. 4583-4588. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10021129)

Will, J., Thamsen, L., Bader, J., Scheinert, D. and Kao, O. (2023) Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing. In: 2022 IEEE International Conference on Big Data, Osaka, Japan, 17-20 December 2022, pp. 161-169. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10020295)

2022

Trihinas, D., Thamsen, L., Beilharz, J. and Symeonides, M. (2022) Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, pp. 29-35. ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00011)

Will, J., Thamsen, L., Bader, J., Scheinert, D. and Kao, O. (2022) Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00014)

Zhu, H., Scheinert, D., Thamsen, L., Gontarska, K. and Kao, O. (2022) Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, pp. 150-159. ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00023)

Bader, J., Lehmann, F., Groth, A., Thamsen, L., Scheinert, D., Will, J., Leser, U. and Kao, O. (2022) Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures. In: 41st IEEE International Performance, Computing, and Communications Conference (IPCCC 2022), Austin, TX, USA, 11-13 November 2022, pp. 269-274. ISBN 9781665480185 (doi: 10.1109/IPCCC55026.2022.9894299)

Geldenhuys, M. K., Pfister, B. J. J., Scheinert, D., Thamsen, L. and Kao, O. (2022) Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing. In: 17th Conference On Computer Science And Intelligence Systems (FedCSIS 2022), Sofia, Bulgaria, 4-7 September 2022, pp. 553-561. ISBN 9788396242396 (doi: 10.15439/2022F225)

Geldenhuys, M. K., Scheinert, D., Kao, O. and Thamsen, L. (2022) Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads. In: IEEE International Conference on Web Services (ICWS 2022), Barcelona, Spain, 11-15 July 2022, pp. 198-207. ISBN 9781665481434 (doi: 10.1109/ICWS55610.2022.00041)

Bader, J., Lehmann, F., Thamsen, L., Will, J., Leser, U. and Kao, O. (2022) Lotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters. In: 34th International Conference on Scientific and Statistical Database Management (SSDBM 2022), Copenhagen, Denmark, 6-8 July 2022, ISBN 9781450396677 (doi: 10.1145/3538712.3538739)

Wiesner, P., Scheinert, D., Wittkopp, T., Thamsen, L. and Kao, O. (2022) Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads. In: 28th International European Conference on Parallel and Distributed Computing (EURO-PAR 2022), Glasgow, Scotland, United Kingdom, 22-26 August 2022, pp. 218-232. ISBN 9783031125966 (doi: 10.1007/978-3-031-12597-3_14)

Thamsen, L., Scheinert, D., Will, J., Bader, J. and Kao, O. (2022) Collaborative cluster configuration for distributed data-parallel processing: a research overview. Datenbank-Spektrum, 22(2), pp. 143-151. (doi: 10.1007/s13222-022-00416-z)

Pfister, B. J. J., Lickefett, W. S., Nitschke, J., Paul, S., Geldenhuys, M. K., Scheinert, D., Gontarska, K. and Thamsen, L. (2022) Rafiki: Task-level Capacity Planning in Distributed Stream Processing Systems. In: 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021), 30 August – 3 September 2021, pp. 352-363. ISBN 9783031061554 (doi: 10.1007/978-3-031-06156-1_28)

Bermbach, D., Bader, J., Hasenburg, J., Pfandzelter, T. and Thamsen, L. (2022) AuctionWhisk: using an auction-inspired approach for function placement in serverless fog platforms. Software: Practice and Experience, 52(5), pp. 1143-1169. (doi: 10.1002/spe.3058)

Habenicht, D., Kreutz, K., Becker, S., Bader, J., Thamsen, L. and Kao, O. (2022) SyncMesh: Improving Data Locality for Function-as-a-Service in Meshed Edge Networks. In: 5th International Workshop on Edge Systems, Analytics and Networking (EdgeSys' 22), Rennes, France, 05 Apr 2022, pp. 55-60. ISBN 9781450392532 (doi: 10.1145/3517206.3526275)

Blumschein, C., Behnke, I., Thamsen, L. and Kao, O. (2022) Differentiating Network Flows for Priority-Aware Scheduling of Incoming Packets in Real-Time IoT Systems. In: 2022 IEEE 25th International Symposium on Real-Time Distributed Computing (ISORC), Västerås, Sweden, 17-18 May 2022, ISBN 9781665406277 (doi: 10.1109/ISORC52572.2022.9812841)

Behnke, I., Wiesner, P., Danicki, R. and Thamsen, L. (2022) A Priority-Aware Multiqueue NIC Design for Real-Time IoT Devices. In: 37th ACM/SIGAPP Symposium on Applied Computing (SAC), Virtual Event, 25 - 29 April 2022, pp. 534-538. ISBN 9781450387132 (doi: 10.1145/3477314.3507165)

Thamsen, L., Beilharz, J., Polze, A. and Kao, O. (2022) The Methods of Cloud Computing. Technical Report. Technische Universität Berlin DepositOnce. (doi: 10.14279/depositonce-15190).

2021

Wiesner, P., Behnke, I., Scheinert, D., Gontarska, K. and Thamsen, L. (2021) Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. In: 22nd International Middleware Conference (Middleware '21), 06-10 Dec 2021, pp. 260-272. ISBN 9781450385343 (doi: 10.1145/3464298.3493399)

Bader, J., Thamsen, L., Kulagina, S., Will, J., Meyerhenke, H. and Kao, O. (2021) Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 65-75. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671519)

Scheinert, D., Alamgiralem, A., Bader, J., Will, J., Wittkopp, T. and Thamsen, L. (2021) On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 3113-3118. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671275)

Will, J., Arslan, O., Bader, J., Scheinert, D. and Thamsen, L. (2021) Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 3141-3146. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671742)

Geldenhuys, M. K., Will, J., Pfister, B. J.J., Haug, M., Scharmann, A. and Thamsen, L. (2021) Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures. In: 1st International Workshop on Testing Distributed Internet of Things Systems (TDIS) at 9th IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 244-250. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00041)

Gontarska, K., Geldenhuys, M., Scheinert, D., Wiesner, P., Polze, A. and Thamsen, L. (2021) Evaluation of Load Prediction Techniques for Distributed Stream Processing. In: 9th International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 91-98. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00023)

Haug, M., Lorenz, F. and Thamsen, L. (2021) GRAL: Localization of Floating Wireless Sensors in Pipe Networks. In: 1st International Workshop on Testing Distributed Internet of Things Systems (TDIS) at 9th IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 251-257. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00042)

Becker, S., Schmidt, F., Thamsen, L., Ferrer, A. J. and Kao, O. (2021) LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks. In: 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 27 Sep - 01 Oct 2021, pp. 41-50. ISBN 9781665412612 (doi: 10.1109/ACSOS52086.2021.00033)

Bermbach, B., Chandra, A., Krintz, C., Gokhale, A., Slominski, A., Thamsen, L., Cavalcante, E., Guo, T., Brandic, I. and Wolski, R. (2021) On the Future of Cloud Engineering. In: 2021 IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 264-275. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00044)

Scheinert, D., Zhu, H., Thamsen, L., Geldenhuys, M. K., Will, J., Acker, A. and Kao, O. (2021) Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs Using Graph Propagation. In: 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), 29-31 Oct 2021, ISBN 9781665443319 (doi: 10.1109/IPCCC51483.2021.9679361)

Will, J., Thamsen, L., Scheinert, D., Bader, J. and Kao, O. (2021) C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. In: 2021 IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 43-52. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00018)

Thamsen, L., Beilharz, J., Tran, V. T., Nedelkoski, S. and Kao, O. (2021) Mary, Hugo, and Hugo*: learning to schedule distributed data-parallel processing jobs on shared clusters. Concurrency and Computation: Practice and Experience, 33(18), e5823. (doi: 10.1002/cpe.5823)

Scheinert, D., Thamsen, L., Zhu, H., Will, J., Acker, A., Wittkopp, T. and Kao, O. (2021) Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. In: 2021 IEEE International Conference on Cluster Computing (CLUSTER), 07-10 Sep 2021, pp. 261-270. ISBN 9781728196664 (doi: 10.1109/Cluster48925.2021.00052)

Tilcher, D. K., Popescu, F., Sommer, H., Thamsen, L. and Thamsen, P. U. (2021) Control Optimization Through Prediction-Based Wastewater Management. In: ASME 2021 Fluids Engineering Division Summer Meeting, 10-12 Aug 2021, ISBN 9780791885291 (doi: 10.1115/FEDSM2021-65375)

Gontarska, K., Wrazen, W., Beilharz, J., Schmid, R., Thamsen, L. and Polze, A. (2021) Predicting Medical Interventions From Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. In: 19th Conference on Artificial Intelligence in Medicine (AIME'21), 15-18 Jun 2021, pp. 293-297. ISBN 9783030772109 (doi: 10.1007/978-3-030-77211-6_33)

Danicki, R., Haug, M., Behnke, I., Mädje, L. and Thamsen, L. (2021) Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems. In: 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2021), Online, United Kingdom, 26 April 2021, pp. 25-30. ISBN 9781450382915 (doi: 10.1145/3434770.3459733)

Beilharz, J., Wiesner, P., Boockmeyer, A., Brokhausen, F., Behnke, I., Schmid, R., Pirl, L. and Thamsen, L. (2021) Towards a Staging Environment for the Internet of Things. In: 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Workshops), 22-26 Mar 2021, pp. 312-315. ISBN 9781665404242 (doi: 10.1109/PerComWorkshops51409.2021.9431087)

Beilharz, J., Wiesner, P., Boockmeyer, A., Friedenberger, D., Brokhausen, F., Pirl, L., Behnke, I., Polze, A. and Thamsen, L. (2021) Continuously Testing Distributed IoT Systems: An Overview of the State of the Art. 19th International Conference on Service-Oriented Computing (ICSOC) Workshops, Virtual Event, 22–25 November 2021.

Bender, F., Brune, J. J., Keutel, N. L., Behnke, I. and Thamsen, L. (2021) PIERES: A Playground for Network Interrupt Experiments on Real-Time Embedded Systems in the IoT. In: 9th International Workshop on Load Testing and Benchmarking of Software Systems (LTB) at the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), 19 - 23 April 2021, pp. 81-84. ISBN 9781450383318 (doi: 10.1145/3447545.3451189)

Chen, S., Brokhausen, F., Wiesner, P., Thamsen, L. and Cominola, A. (2021) Assessing the Resilience of Water Distribution Networks Under Different Sensor Network Architectures and Data Sampling Frequencies. In: 2nd International Symposium on Water System Operations (ISWSO), Bristol, United Kingdom, 1-3 September 2021,

Ferrer, A. J., Becker, S., Schmidt, F., Thamsen, L. and Kao, O. (2021) Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms. In: 1st Workshop on the Cloud-to-Things Continuum (Cloud2Things) at 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Melbourne, Australia, 10-13 May 2021, pp. 634-641. ISBN 9781728195865 (doi: 10.1109/CCGrid51090.2021.00076)

Scheinert, D., Acker, A., Thamsen, L., Geldenhuys, M. K. and Kao, O. (2021) Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies. In: 2nd Workshop on Cloud Intelligence (CloudIntelligence) at the 43th International Conference on Software Engineering (ICSE), 29 May 2021, pp. 7-12. ISBN 9781665445634 (doi: 10.1109/CloudIntelligence52565.2021.00011)

Wiesner, P. and Thamsen, L. (2021) LEAF: Simulating Large Energy-Aware Fog Computing Environments. In: 2021 5th IEEE International Conference on Fog and Edge Computing (ICFEC), Melbourne, Australia, 10-13 May 2021, pp. 29-36. ISBN 9781665402910 (doi: 10.1109/ICFEC51620.2021.00012)

2020

Geldenhuys, M., Thamsen, L. and Kao, O. (2020) Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 434-440. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9378474)

Lorenz, F., Geldenhuys, M., Sommer, H., Jakobs, F., Lüring, C., Skwarek, V., Behnke, I. and Thamsen, L. (2020) A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 3488-3493. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9378138)

Will, J., Bader, J. and Thamsen, L. (2020) Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 2851-2856. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9377994)

Behnke, I., Pirl, L., Thamsen, L., Danicki, R., Polze, A. and Kao, O. (2020) Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet? In: 2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC), 06-08 Nov 2020, ISBN 9781728198293 (doi: 10.1109/IPCCC50635.2020.9391536)

Lorenz, F., Thamsen, L., Wilke, A., Behnke, I., Waldmüller-Littke, J., Komarov, I., Kao, O. and Paeschke, M. (2020) Fingerprinting Analog IoT Sensors for Secret-Free Authentication. In: 2020 29th International Conference on Computer Communications and Networks (ICCCN), 03-06 Aug 2020, ISBN 9781728166070 (doi: 10.1109/ICCCN49398.2020.9209643)

2018

Thamsen, L., Renner, T., Verbitskiy, I. and Kao, O. (2018) Adaptive Resource Management for Distributed Data Analytics. In: Grandinetti, L., Mirtaheri, S. L., Shahbazian, R., Sterling, T. and Voevodin, V. (eds.) Big Data and HPC: Ecosystem and Convergence. Series: Advances in Parallel Computing. IOS Press: Amsterdam, pp. 155-170. ISBN 9781614998815 (doi: 10.3233/978-1-61499-882-2-155)

2017

Thamsen, L., Rabier, B., Schmidt, F., Renner, T. and Kao, O. (2017) Scheduling Recurring Distributed Dataflow Jobs Based on Resource Utilization and Interference. In: 2017 IEEE International Congress on Big Data (BigData Congress), Honolulu, HI, USA, 25-30 June 2017, pp. 145-152. ISBN 9781538619964 (doi: 10.1109/BigDataCongress.2017.28)

2016

Thamsen, L., Steinert, B. and Hirschfeld, R. (2016) Preserving Access to Previous System States in the Lively Kernel. In: Plattner, H., Meinel, C. and Leifer, L. (eds.) Design Thinking Research: Making Design Thinking Foundational. Series: Understanding Innovation. Springer: Cham, pp. 235-264. ISBN 9783319196404 (doi: 10.1007/978-3-319-19641-1_15)

This list was generated on Mon Jun 5 01:20:53 2023 BST.
Jump to: Articles | Book Sections | Research Reports or Papers | Conference or Workshop Item | Conference Proceedings
Number of items: 51.

Articles

Behnke, I., Blumschein, C., Danicki, R., Wiesner, P., Thamsen, L. and Kao, O. (2023) Towards a real-time IoT: approaches for incoming packet processing in cyber-physical systems. Journal of Systems Architecture, (doi: 10.1016/j.sysarc.2023.102891) (In Press)

Thamsen, L., Scheinert, D., Will, J., Bader, J. and Kao, O. (2022) Collaborative cluster configuration for distributed data-parallel processing: a research overview. Datenbank-Spektrum, 22(2), pp. 143-151. (doi: 10.1007/s13222-022-00416-z)

Bermbach, D., Bader, J., Hasenburg, J., Pfandzelter, T. and Thamsen, L. (2022) AuctionWhisk: using an auction-inspired approach for function placement in serverless fog platforms. Software: Practice and Experience, 52(5), pp. 1143-1169. (doi: 10.1002/spe.3058)

Thamsen, L., Beilharz, J., Tran, V. T., Nedelkoski, S. and Kao, O. (2021) Mary, Hugo, and Hugo*: learning to schedule distributed data-parallel processing jobs on shared clusters. Concurrency and Computation: Practice and Experience, 33(18), e5823. (doi: 10.1002/cpe.5823)

Book Sections

Thamsen, L., Renner, T., Verbitskiy, I. and Kao, O. (2018) Adaptive Resource Management for Distributed Data Analytics. In: Grandinetti, L., Mirtaheri, S. L., Shahbazian, R., Sterling, T. and Voevodin, V. (eds.) Big Data and HPC: Ecosystem and Convergence. Series: Advances in Parallel Computing. IOS Press: Amsterdam, pp. 155-170. ISBN 9781614998815 (doi: 10.3233/978-1-61499-882-2-155)

Thamsen, L., Steinert, B. and Hirschfeld, R. (2016) Preserving Access to Previous System States in the Lively Kernel. In: Plattner, H., Meinel, C. and Leifer, L. (eds.) Design Thinking Research: Making Design Thinking Foundational. Series: Understanding Innovation. Springer: Cham, pp. 235-264. ISBN 9783319196404 (doi: 10.1007/978-3-319-19641-1_15)

Research Reports or Papers

Thamsen, L., Beilharz, J., Polze, A. and Kao, O. (2022) The Methods of Cloud Computing. Technical Report. Technische Universität Berlin DepositOnce. (doi: 10.14279/depositonce-15190).

Conference or Workshop Item

Beilharz, J., Wiesner, P., Boockmeyer, A., Friedenberger, D., Brokhausen, F., Pirl, L., Behnke, I., Polze, A. and Thamsen, L. (2021) Continuously Testing Distributed IoT Systems: An Overview of the State of the Art. 19th International Conference on Service-Oriented Computing (ICSOC) Workshops, Virtual Event, 22–25 November 2021.

Conference Proceedings

Lehmann, F., Bader, J., Tschirpke, F., Thamsen, L. and Leser, U. (2023) How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow Scheduling Interface. In: 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023), Bangalore, India, 1-4 May 2023, (Accepted for Publication)

Scheinert, D., Becker, S., Bader, J., Thamsen, L., Will, J. and Kao, O. (2023) Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics. In: 2022 IEEE International Conference on Big Data, Osaka, Japan, 17-20 December 2022, pp. 209-216. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10020860)

Scheinert, D., Zadeh Aghdam, B. S., Becker, S., Kao, O. and Thamsen, L. (2023) Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments. In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), Osaka, Japan, 17-20 Dec 2022, pp. 4583-4588. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10021129)

Will, J., Thamsen, L., Bader, J., Scheinert, D. and Kao, O. (2023) Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing. In: 2022 IEEE International Conference on Big Data, Osaka, Japan, 17-20 December 2022, pp. 161-169. ISBN 9781665480451 (doi: 10.1109/BigData55660.2022.10020295)

Trihinas, D., Thamsen, L., Beilharz, J. and Symeonides, M. (2022) Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, pp. 29-35. ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00011)

Will, J., Thamsen, L., Bader, J., Scheinert, D. and Kao, O. (2022) Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00014)

Zhu, H., Scheinert, D., Thamsen, L., Gontarska, K. and Kao, O. (2022) Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning. In: 10th IEEE International Conference on Cloud Engineering (IC2E), California, USA, 26-30 Sept 2022, pp. 150-159. ISBN 9781665491150 (doi: 10.1109/IC2E55432.2022.00023)

Bader, J., Lehmann, F., Groth, A., Thamsen, L., Scheinert, D., Will, J., Leser, U. and Kao, O. (2022) Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures. In: 41st IEEE International Performance, Computing, and Communications Conference (IPCCC 2022), Austin, TX, USA, 11-13 November 2022, pp. 269-274. ISBN 9781665480185 (doi: 10.1109/IPCCC55026.2022.9894299)

Geldenhuys, M. K., Pfister, B. J. J., Scheinert, D., Thamsen, L. and Kao, O. (2022) Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing. In: 17th Conference On Computer Science And Intelligence Systems (FedCSIS 2022), Sofia, Bulgaria, 4-7 September 2022, pp. 553-561. ISBN 9788396242396 (doi: 10.15439/2022F225)

Geldenhuys, M. K., Scheinert, D., Kao, O. and Thamsen, L. (2022) Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads. In: IEEE International Conference on Web Services (ICWS 2022), Barcelona, Spain, 11-15 July 2022, pp. 198-207. ISBN 9781665481434 (doi: 10.1109/ICWS55610.2022.00041)

Bader, J., Lehmann, F., Thamsen, L., Will, J., Leser, U. and Kao, O. (2022) Lotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters. In: 34th International Conference on Scientific and Statistical Database Management (SSDBM 2022), Copenhagen, Denmark, 6-8 July 2022, ISBN 9781450396677 (doi: 10.1145/3538712.3538739)

Wiesner, P., Scheinert, D., Wittkopp, T., Thamsen, L. and Kao, O. (2022) Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads. In: 28th International European Conference on Parallel and Distributed Computing (EURO-PAR 2022), Glasgow, Scotland, United Kingdom, 22-26 August 2022, pp. 218-232. ISBN 9783031125966 (doi: 10.1007/978-3-031-12597-3_14)

Pfister, B. J. J., Lickefett, W. S., Nitschke, J., Paul, S., Geldenhuys, M. K., Scheinert, D., Gontarska, K. and Thamsen, L. (2022) Rafiki: Task-level Capacity Planning in Distributed Stream Processing Systems. In: 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021), 30 August – 3 September 2021, pp. 352-363. ISBN 9783031061554 (doi: 10.1007/978-3-031-06156-1_28)

Habenicht, D., Kreutz, K., Becker, S., Bader, J., Thamsen, L. and Kao, O. (2022) SyncMesh: Improving Data Locality for Function-as-a-Service in Meshed Edge Networks. In: 5th International Workshop on Edge Systems, Analytics and Networking (EdgeSys' 22), Rennes, France, 05 Apr 2022, pp. 55-60. ISBN 9781450392532 (doi: 10.1145/3517206.3526275)

Blumschein, C., Behnke, I., Thamsen, L. and Kao, O. (2022) Differentiating Network Flows for Priority-Aware Scheduling of Incoming Packets in Real-Time IoT Systems. In: 2022 IEEE 25th International Symposium on Real-Time Distributed Computing (ISORC), Västerås, Sweden, 17-18 May 2022, ISBN 9781665406277 (doi: 10.1109/ISORC52572.2022.9812841)

Behnke, I., Wiesner, P., Danicki, R. and Thamsen, L. (2022) A Priority-Aware Multiqueue NIC Design for Real-Time IoT Devices. In: 37th ACM/SIGAPP Symposium on Applied Computing (SAC), Virtual Event, 25 - 29 April 2022, pp. 534-538. ISBN 9781450387132 (doi: 10.1145/3477314.3507165)

Wiesner, P., Behnke, I., Scheinert, D., Gontarska, K. and Thamsen, L. (2021) Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. In: 22nd International Middleware Conference (Middleware '21), 06-10 Dec 2021, pp. 260-272. ISBN 9781450385343 (doi: 10.1145/3464298.3493399)

Bader, J., Thamsen, L., Kulagina, S., Will, J., Meyerhenke, H. and Kao, O. (2021) Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 65-75. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671519)

Scheinert, D., Alamgiralem, A., Bader, J., Will, J., Wittkopp, T. and Thamsen, L. (2021) On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 3113-3118. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671275)

Will, J., Arslan, O., Bader, J., Scheinert, D. and Thamsen, L. (2021) Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. In: 2021 IEEE International Conference on Big Data (Big Data), 15-18 Dec 2021, pp. 3141-3146. ISBN 9781665439022 (doi: 10.1109/BigData52589.2021.9671742)

Geldenhuys, M. K., Will, J., Pfister, B. J.J., Haug, M., Scharmann, A. and Thamsen, L. (2021) Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures. In: 1st International Workshop on Testing Distributed Internet of Things Systems (TDIS) at 9th IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 244-250. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00041)

Gontarska, K., Geldenhuys, M., Scheinert, D., Wiesner, P., Polze, A. and Thamsen, L. (2021) Evaluation of Load Prediction Techniques for Distributed Stream Processing. In: 9th International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 91-98. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00023)

Haug, M., Lorenz, F. and Thamsen, L. (2021) GRAL: Localization of Floating Wireless Sensors in Pipe Networks. In: 1st International Workshop on Testing Distributed Internet of Things Systems (TDIS) at 9th IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 251-257. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00042)

Becker, S., Schmidt, F., Thamsen, L., Ferrer, A. J. and Kao, O. (2021) LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks. In: 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 27 Sep - 01 Oct 2021, pp. 41-50. ISBN 9781665412612 (doi: 10.1109/ACSOS52086.2021.00033)

Bermbach, B., Chandra, A., Krintz, C., Gokhale, A., Slominski, A., Thamsen, L., Cavalcante, E., Guo, T., Brandic, I. and Wolski, R. (2021) On the Future of Cloud Engineering. In: 2021 IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 264-275. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00044)

Scheinert, D., Zhu, H., Thamsen, L., Geldenhuys, M. K., Will, J., Acker, A. and Kao, O. (2021) Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs Using Graph Propagation. In: 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), 29-31 Oct 2021, ISBN 9781665443319 (doi: 10.1109/IPCCC51483.2021.9679361)

Will, J., Thamsen, L., Scheinert, D., Bader, J. and Kao, O. (2021) C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. In: 2021 IEEE International Conference on Cloud Engineering (IC2E), 04-08 Oct 2021, pp. 43-52. ISBN 9781665449700 (doi: 10.1109/IC2E52221.2021.00018)

Scheinert, D., Thamsen, L., Zhu, H., Will, J., Acker, A., Wittkopp, T. and Kao, O. (2021) Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. In: 2021 IEEE International Conference on Cluster Computing (CLUSTER), 07-10 Sep 2021, pp. 261-270. ISBN 9781728196664 (doi: 10.1109/Cluster48925.2021.00052)

Tilcher, D. K., Popescu, F., Sommer, H., Thamsen, L. and Thamsen, P. U. (2021) Control Optimization Through Prediction-Based Wastewater Management. In: ASME 2021 Fluids Engineering Division Summer Meeting, 10-12 Aug 2021, ISBN 9780791885291 (doi: 10.1115/FEDSM2021-65375)

Gontarska, K., Wrazen, W., Beilharz, J., Schmid, R., Thamsen, L. and Polze, A. (2021) Predicting Medical Interventions From Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. In: 19th Conference on Artificial Intelligence in Medicine (AIME'21), 15-18 Jun 2021, pp. 293-297. ISBN 9783030772109 (doi: 10.1007/978-3-030-77211-6_33)

Danicki, R., Haug, M., Behnke, I., Mädje, L. and Thamsen, L. (2021) Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems. In: 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2021), Online, United Kingdom, 26 April 2021, pp. 25-30. ISBN 9781450382915 (doi: 10.1145/3434770.3459733)

Beilharz, J., Wiesner, P., Boockmeyer, A., Brokhausen, F., Behnke, I., Schmid, R., Pirl, L. and Thamsen, L. (2021) Towards a Staging Environment for the Internet of Things. In: 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Workshops), 22-26 Mar 2021, pp. 312-315. ISBN 9781665404242 (doi: 10.1109/PerComWorkshops51409.2021.9431087)

Bender, F., Brune, J. J., Keutel, N. L., Behnke, I. and Thamsen, L. (2021) PIERES: A Playground for Network Interrupt Experiments on Real-Time Embedded Systems in the IoT. In: 9th International Workshop on Load Testing and Benchmarking of Software Systems (LTB) at the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), 19 - 23 April 2021, pp. 81-84. ISBN 9781450383318 (doi: 10.1145/3447545.3451189)

Chen, S., Brokhausen, F., Wiesner, P., Thamsen, L. and Cominola, A. (2021) Assessing the Resilience of Water Distribution Networks Under Different Sensor Network Architectures and Data Sampling Frequencies. In: 2nd International Symposium on Water System Operations (ISWSO), Bristol, United Kingdom, 1-3 September 2021,

Ferrer, A. J., Becker, S., Schmidt, F., Thamsen, L. and Kao, O. (2021) Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms. In: 1st Workshop on the Cloud-to-Things Continuum (Cloud2Things) at 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Melbourne, Australia, 10-13 May 2021, pp. 634-641. ISBN 9781728195865 (doi: 10.1109/CCGrid51090.2021.00076)

Scheinert, D., Acker, A., Thamsen, L., Geldenhuys, M. K. and Kao, O. (2021) Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies. In: 2nd Workshop on Cloud Intelligence (CloudIntelligence) at the 43th International Conference on Software Engineering (ICSE), 29 May 2021, pp. 7-12. ISBN 9781665445634 (doi: 10.1109/CloudIntelligence52565.2021.00011)

Wiesner, P. and Thamsen, L. (2021) LEAF: Simulating Large Energy-Aware Fog Computing Environments. In: 2021 5th IEEE International Conference on Fog and Edge Computing (ICFEC), Melbourne, Australia, 10-13 May 2021, pp. 29-36. ISBN 9781665402910 (doi: 10.1109/ICFEC51620.2021.00012)

Geldenhuys, M., Thamsen, L. and Kao, O. (2020) Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 434-440. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9378474)

Lorenz, F., Geldenhuys, M., Sommer, H., Jakobs, F., Lüring, C., Skwarek, V., Behnke, I. and Thamsen, L. (2020) A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 3488-3493. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9378138)

Will, J., Bader, J. and Thamsen, L. (2020) Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs. In: 2020 IEEE International Conference on Big Data (Big Data), 10-13 Dec 2020, pp. 2851-2856. ISBN 9781728162515 (doi: 10.1109/BigData50022.2020.9377994)

Behnke, I., Pirl, L., Thamsen, L., Danicki, R., Polze, A. and Kao, O. (2020) Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet? In: 2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC), 06-08 Nov 2020, ISBN 9781728198293 (doi: 10.1109/IPCCC50635.2020.9391536)

Lorenz, F., Thamsen, L., Wilke, A., Behnke, I., Waldmüller-Littke, J., Komarov, I., Kao, O. and Paeschke, M. (2020) Fingerprinting Analog IoT Sensors for Secret-Free Authentication. In: 2020 29th International Conference on Computer Communications and Networks (ICCCN), 03-06 Aug 2020, ISBN 9781728166070 (doi: 10.1109/ICCCN49398.2020.9209643)

Thamsen, L., Rabier, B., Schmidt, F., Renner, T. and Kao, O. (2017) Scheduling Recurring Distributed Dataflow Jobs Based on Resource Utilization and Interference. In: 2017 IEEE International Congress on Big Data (BigData Congress), Honolulu, HI, USA, 25-30 June 2017, pp. 145-152. ISBN 9781538619964 (doi: 10.1109/BigDataCongress.2017.28)

This list was generated on Mon Jun 5 01:20:53 2023 BST.

Grants

  • I developed over a dozen successful project grants under Prof. Odej Kao at TU Berlin as a postdoc and senior researcher:
    • I am currently still part of the DFG-funded collaborative research center FONDA (until 2024) and the DAAD-funded European teaching network ide3a (until 2023).
    • I will be part of another DFG-funded research project on "C5: Collaborative and Cross-Context Cluster Configuration for Distributed Data-Parallel Processing", working with an RA at TU Berlin from next year until 2026.
    • Previously, I was involved in grant-funded projects in the research centers BIFOLD and BBDC (BMBF), the interdisciplinary projects WaterGridSense (BMBF), OPTIMA (EU Regional Development Fund), and Telemed5000 (BMWi), and the HEIBRiDS graduate school (Helmholtz Association).
    • I also helped acquire and lead an industry collaboration with Bundesdruckerei GmbH.
  • I am currently developing new research at the University of Glasgow and am actively looking for new collaborators.

Supervision

Currently:

Previously:

  • I have worked closely with PhD students at TU Berlin (in the Distributed and Operating Systems group of Prof. Odej Kao), HPI (in the Operating Systems and Middleware group of Prof. Andreas Polze), and HU Berlin (in the Knowledge Management in Bioinformatics group of Prof. Ulf Leser) as a postdoc and senior researcher at TU Berlin as well as a guest professor at HU Berlin.
  • I (co)-supervised over two dozen successful bachelor and master theses at TU Berlin, HPI, and HU Berlin over the last ten years. In addition, I have (co-)supervised ten semester-long student team projects at these institutions.
  • I have acted as a supervisor for four successful MSc dissertation projects at the University of Glasgow.

Teaching

I have been involved in teaching the basics of distributed systems, operating systems, and systems engineering as well as related advanced topics such as cloud computing and big data systems.

A full list of lectures, seminars, team projects, interdisciplinary courses, and extracurricular teaching can be found at https://lauritzthamsen.org/teaching/.

Additional information

You can usually find me in S152 in the School of Computing Science (2nd floor, 15 Lilybank Gardens, accessible through the Sir Alwyn Williams Building, 18 Lilybank Gardens). When I am in the office, you can reach me via +44 141 330 2000 (x0652).

I am part of the student conduct team of the School of Computing Science, coordinating cases of academic misconduct together with Richard McCreadie (yet currently transitioning this role onwards to Emma Li and Paul Siebert).

I have been nominated as the School of Computing Science’s adviser for sustainability in the curriculum. In this role, I support the integration of low-carbon and sustainable computing topics into the School's teaching.

Together with colleagues, I offer disability office hours. We organize these in each semester and they are open to the students of all our programs.

I help with CompuMatch requests, which is a service provided by the School to match scientists of other disciplines with computer scientists to foster new and exciting research collaborations.


A profile photo of Dr Lauritz Thamsen