Publications of Boris Koldehofe
Recent Publications
- Network Testing Utilizing ProgrammableNetworking Hardware. (), In IEEE Communications Magazine, IEEE, 2022.
- Enhancing Flexibility for Dynamic Time-Sensitive Network Configurations (), In Proceedings of the 3rd KuVS Fachgespräch on Network Softwarization, Universität Tübingen, 2022.
- On the Incremental Reconfiguration of Time-sensitive Networks at Runtime (), In Proceedings of the IFIP Networking Conference., IFIP, 2022.
BibTeX
- Travel light: state shedding for efficient operator migration (), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (DEBS'22), ACM press, 2022.
- FA2: Fast, Accurate Autoscaling for Serving Deep Learning Inference with SLA Guarantees (), In Proceedings of the 28th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2022), IEEE, 2022.
BibTeX
- PANDA: performance prediction for parallel and dynamic stream processing (), In Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems, ACM press, 2022.
- Window-based Parallel Operator Execution with In-Network Computing: Proceedings (), In Proceedings of the 16th ACM International Conference on Distributed and Event-based Systems (DEBS '22), ACM New York, NY, USA, 2022.
Abstract
Data parallel processing is a key concept to increase the scalability and elasticity in event streaming systems. Often data parallelism is accomplished in a splitter-merger architecture where the splitter divides incoming streams into partitions and forwards them to parallel operator instances. The splitter performance is a limiting factor to the system throughput and the parallelization degree.This work studies how to leverage novel methods of in-network computing to accelerate the splitter functionality by implementing it as an in-network function. While dedicated hardware for in-network computing has a high potential to enhance the splitter performance, in-network programming models like the P4 language are also highly limited in their expressiveness to support corresponding parallelization models. We propose P4SS which supports overlapping and non-overlapping count-based windows for multiple independent data streams and parallelizes them to a dynamically configurable number of operator instances. We validate in the context of a prototypical implementation our splitting strategy and its scalability in terms of switch resource consumption.
Keywords: Data Parallelism, In-network Computing, Load Balancing, Complex Event Processing (CEP), P4 Language, Data Plane ProgrammingBibTeX
doi - TCEP: Transitions in Operator Placement to Adapt to Dynamic Network Environments. (), In In Journal of Computer and Systems Sciences (JCSS), Special Issue on Algorithmic Theory of Dynamic Networks and its Applications., Elsevier, volume 122, 2021.
- OpenBNG: Central office network functions on programmable data plane hardware (), In International Journal of Network Management, Wiley, volume 31, 2021.
- Leveraging Flexibility of Time-Sensitive Networks for dynamic Reconfigurability (), In Proceedings of IFIP Networking 2021, IFIP, 2021.
- Leveraging PIFO Queues for Scheduling in Time-Sensitive Networks (), In In the Proceedings of the IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2021)., IEEE, 2021.
- P4-CoDel: Experiences on Programmable Data Plane Hardware (), In Proceedings of the IEEE International Conference on Communications (ICC 2021): Next-Generation Networking and Internet Symposium, IEEE, 2021.
- Towards QoE-Driven Optimization of Multi-Dimensional Content Streaming (), In Proceedings of the Conference on Networked Systems 2021 (NetSys 2021), European Association of Software Science and Technology, 2021.
- OpenBNG: Central office network functions on programmable data plane hardware (), In International Journal of Network Management, Wiley, 2020.
- Grußwort der Gastherausgeber zum Thema Fog Computing (), In Informatik Spektrum, Springer Science and Business Media LLC, volume 42, 2020.
- Operator as a Service: Stateful Serverless Complex Event Processing (), In Proceedings of the 2020 IEEE International Conference on Big Data, IEEE, 2020.
- Microbursts in Software and Hardware-based Traffic Load Generation (), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2020.
- Flexible Content-based Publish/Subscribe over Programmable Data Planes (), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2020.
- P4STA: High Performance Packet Timestamping with Programmable Packet Processors (), In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2020.