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 new Lecturer in the School of Computing Science (SoCS) at University of Glasgow, where I work on Resource-Efficient Distributed Computing with a focus on resource management and data-intensive applications.

Within SoCS, I am a member of the Glasgow Systems Section (GLASS) and the Glasgow Parallelism Group (GPG) and I am part of the School's research towards Low-Carbon and Sustainable Computing (LC-SC).

I currently co-lead the collaboration on Adaptive Resource Management for Data-Intensive Applications with TU Berlin and I started the Distributed Systems Engineering Lab (diselab) with researchers from TU Berlin and HPI (at University of Potsdam) in 2020, in which we jointly investigate the dependability and efficiency of distributed applications in the heterogeneous and dynamic computing environments of the Internet of Things.

Before joining University of Glasgow, I was a guest professor in the Department of Computer Science at HU Berlin, substituting for Prof. Ulf Leser and teaching Data-Intensive Systems, and a senior researcher in the Distributed and Operating Systems group at TU Berlin, leading the research on Adaptive Resource Management and lecturing on Cloud Computing and Distributed Systems. At TU Berlin, I also completed a postdoc and did my PhD under Prof. Odej Kao, working on resource management 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, and at Signavio in Berlin.

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

Research interests

I am keen on making distributed computing more accessible and sustainable. To this end, I work towards easy-to-use, yet resource-efficient and resilient distributed computing systems, focusing especially on resource management and data-intensive applications.

My research interests include:

  • Edge and Cloud Computing
  • Resource Management and Scheduling
  • Carbon-Aware and Sustainable Computing
  • Distributed Computing Systems
  • Data-Intensive Applications

Publications

List by: Type | Date

Jump to: 2022 | 2021
Number of items: 16.

2022

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, (Accepted for Publication)

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 (Accepted for Publication)

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)

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)

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)

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)

This list was generated on Wed May 25 03:24:15 2022 BST.
Jump to: Articles | Research Reports or Papers | Conference Proceedings
Number of items: 16.

Articles

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)

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 Proceedings

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, (Accepted for Publication)

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 (Accepted for Publication)

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)

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)

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)

This list was generated on Wed May 25 03:24:15 2022 BST.

Grants

  • I contributed to over a dozen succesfull project grants under Prof. Odej Kao at TU Berlin as a postdoc and senior researcher:
    • I am currently still part of the DFG-funded research center FONDA and the DAAD-funded European teaching network ide3a.
    • 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 led a direct industry collaboration with Bundesdruckerei GmbH.
  • I was part of a project in the HPI-Stanford Design Thinking Research Program as a PhD-track master student in Robert Hirschfeld's group at HPI, though I did not contribute to the grant proposal. Another project in my time at HPI was a direct collaboration with Bedarra Research Labs.
  • I was selected for several personal stipends before.

Supervision

  • I am looking for PhD students to join me in Glasgow, where I recently started on a permanent academic post, to set up a new lab on Resource-Efficient Distributed Computing (ReDisco).
  • 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 am currently part of the Thesis Advisory Committees of three PhD students at HU Berlin and TU Berlin in context of the DFG Collaborative Research Center FONDA.
  • I (co)-supervised over two dozen bachelor and master theses at TU Berlin, HPI, and HU Berlin over the last ten years.

Teaching

I have been involved in teaching the basics of distributed systems, operating systems, and software engineering as well as advanced topics around cloud computing, data engineering, and the Internet of Things.

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

Additional information

You can usually find me in S 152 in the School's buildings (2nd floor, 15 Liliybank Gardens – though entry to the School is through the Sir Alwyn Williams Building, 18 Lilybank Gardens).


Lauritz Thamsen's profile photo