TU Wien Informatics

20 Years

Role

  • faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms / Raith, P., Rausch, T., Furutanpey, A., & Dustdar, S. (2023). faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms. Software: Practice and Experience, 53(12), 2327–2361. https://doi.org/10.1002/spe.3277
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  • Intent-based Management for the Distributed Computing Continuum / Morichetta, A., Spring, N., Raith, P., & Dustdar, S. (2023). Intent-based Management for the Distributed Computing Continuum. In Proceedings : 17th IEEE International Conference on Service-Oriented System Engineering (IEEE SOSE 2023) (pp. 239–249). IEEE. https://doi.org/10.1109/SOSE58276.2023.00035
  • Architectural Vision for Quantum Computing in the Edge-Cloud Continuum / Furutanpey, A., Barzen, J., Bechtold, M., Dustdar, S., Leymann, F., Raith, P., & Truger, F. (2023). Architectural Vision for Quantum Computing in the Edge-Cloud Continuum. In S. Ali, C. Ardagna, N. Atukorala, J. Barzen, C. K. Chang, Chang Rong N., J. Fan, I. Faro, S. Feld, G. Fox, Z. Jin, F. Leymann, F. Neukart, S. de la Puente, & M. Wimmer (Eds.), Proceedings of the IEEE International Conference on Quantum Software (IEEE QSW 2023) (pp. 88–103). IEEE. https://doi.org/10.1109/QSW59989.2023.00021
  • FrankenSplit: Efficient Neural Feature Compression with Shallow Variational Bottleneck Injection for Mobile Edge Computing / Furutanpey, A., Raith, P. A., & Dustdar, S. (2023). FrankenSplit: Efficient Neural Feature Compression with Shallow Variational Bottleneck Injection for Mobile Edge Computing. arXiv. https://doi.org/10.48550/arXiv.2302.10681
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  • Demystifying deep learning in predictive monitoring for cloud-native SLOs / Morichetta, A., Pusztai, T. W., Vij, D., Casamayor Pujol, V., Raith, P. A., Xiong, Y., Nastic, S., Dustdar, S., & Zhang, Z. (2023). Demystifying deep learning in predictive monitoring for cloud-native SLOs. In C. A. ARDAGNA, N. Atukorala, P. Beckmann, C. C. Chang, Chang Rong N., C. Evangelinos, J. Fan, G. Fox, J. Fox, C. Hagleitner, Z. Jin, T. Kosar, & M. Parashar (Eds.), 2023 IEEE 16th International Conference on Cloud Computing (CLOUD) (pp. 1–11). IEEE. https://doi.org/10.1109/CLOUD60044.2023.00013
  • Vela: A 3-Phase Distributed Scheduler for the Edge-Cloud Continuum / Pusztai, T., Nastic, S., Raith, P., Dustdar, S., Vij, D., & Xiong, Y. (2023). Vela: A 3-Phase Distributed Scheduler for the Edge-Cloud Continuum. In Proceedings 2023 IEEE International Conference on Cloud Engineering (IC2E 2023) (pp. 161–172). IEEE. https://doi.org/10.1109/IC2E59103.2023.00026
    Project: RAINBOW (2020–2022)
  • Serverless Edge Computing—Where We Are and What Lies Ahead / Raith, P., Nastic, S., & Dustdar, S. (2023). Serverless Edge Computing—Where We Are and What Lies Ahead. IEEE Internet Computing, 27(3), 50–64. https://doi.org/10.1109/MIC.2023.3260939
  • Polaris Scheduler: SLO- and Topology-aware Microservices Scheduling at the Edge / Pusztai, T., Nastic, S., Morichetta, A., Casamayor Pujol, V., Raith, P., Dustdar, S., Vij, D., Xiong, Y., & Zhang, Z. (2022). Polaris Scheduler: SLO- and Topology-aware Microservices Scheduling at the Edge. In Proceedings 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC 2022) (pp. 61–70). IEEE. https://doi.org/10.1109/UCC56403.2022.00017
    Project: RAINBOW (2020–2022)
  • Mobility-Aware Serverless Function Adaptations Across the Edge-Cloud Continuum / Raith, P., Rausch, T., Dustdar, S., Rossi, F., Cardellini, V., & Ranjan, R. (2022). Mobility-Aware Serverless Function Adaptations Across the Edge-Cloud Continuum. In Proceedings 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC 2022) (pp. 123–132). IEEE. https://doi.org/10.1109/UCC56403.2022.00023
    Project: RAINBOW (2020–2022)
  • A Serverless Computing Fabric for Edge & Cloud / Nastic, S., Raith, P., Furutanpey, A., Pusztai, T., & Dustdar, S. (2022). A Serverless Computing Fabric for Edge & Cloud. In Proceedings 2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI) (pp. 1–12). IEEE. https://doi.org/10.1109/CogMI56440.2022.00011
  • An End-to-End Framework for Benchmarking Edge-Cloud Cluster Management Techniques / Raith, P., Rausch, T., Prüller, P., Furutanpey, A., & Dustdar, S. (2022). An End-to-End Framework for Benchmarking Edge-Cloud Cluster Management Techniques. In 2022 IEEE International Conference on Cloud Engineering (IC2E) (pp. 22–28). IEEE. https://doi.org/10.1109/IC2E55432.2022.00010
  • Container scheduling on heterogeneous clusters using machine learning-based workload characterization / Raith, P. A. (2021). Container scheduling on heterogeneous clusters using machine learning-based workload characterization [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.82862
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  • Edge Intelligence as a Service / Raith, P., & Dustdar, S. (2021). Edge Intelligence as a Service. In B. Carminati, C. K. Chang, E. Damiani, S. Deng, W. Tan, Z. Wang, R. Ward, & J. Zhang (Eds.), 2021 IEEE International Conference on Services Computing (SCC). IEEE. https://doi.org/10.1109/scc53864.2021.00038
  • Towards a new paradigm for managing computing continuum applications / Casamayor Pujol, V., Raith, P., & Dustdar, S. (2021). Towards a new paradigm for managing computing continuum applications. In 2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI) (pp. 180–188). IEEE. https://doi.org/10.1109/cogmi52975.2021.00032
  • Synthesizing Plausible Infrastructure Configurations for Evaluating Edge Computing Systems / Rausch, T., Lachner, C., Frangoudis, P. A., Raith, P., & Dustdar, S. (2020). Synthesizing Plausible Infrastructure Configurations for Evaluating Edge Computing Systems. In I. Ahmad & M. Zhao (Eds.), 3rd USENIX Workshop on Hot Topics in Edge Computing, HotEdge 2020. USENIX Association. http://hdl.handle.net/20.500.12708/58203
  • A system for operating energy-aware cloudlets / Rausch, T., Raith, P., Pillai, P., & Dustdar, S. (2019). A system for operating energy-aware cloudlets. In Proceedings of the 4th ACM/IEEE Symposium on Edge Computing. Demo Session at the 4th ACM/IEEE Symposium on Edge Computing (SEC 2019), Arlington, Virginia, USA, Non-EU. ACM. https://doi.org/10.1145/3318216.3363325