2024W

• Bachelor Thesis for Informatics and Business Informatics / 184.714 / PR
• Distributed Systems / 194.024 / VU
• Project in Computer Science 1 / 194.145 / PR
• Project in Computer Science 2 / 194.146 / PR
• Seminar in Distributed Systems / 184.194 / SE

2025S

• Bachelor Thesis for Informatics and Business Informatics / 184.714 / PR
• Distributed Systems Technologies / 184.260 / VU
• Project in Computer Science 1 / 194.145 / PR
• Project in Computer Science 2 / 194.146 / PR
• Seminar in Distributed Systems / 184.194 / SE

2025

• Towards Multi-dimensional Elasticity for Pervasive Stream Processing Services / Sedlak, B., Morichetta, A., Raith, P., Casamayor Pujol, V., & Dustdar, S. (2025). Towards Multi-dimensional Elasticity for Pervasive Stream Processing Services. arXiv. https://doi.org/10.34726/9061
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  Project: TEADAL (2022–2025)
• Towards Adaptive Asynchronous Federated Learning for Human Activity Recognition / Gajanin, R., Danilenka, A., Morichetta, A., & Nastic, S. (2025). Towards Adaptive Asynchronous Federated Learning for Human Activity Recognition. In E. Peltonen, S. Hyrynsalmi, I. Wagner, J. S. Rellermeyer, & N. Mohan (Eds.), IoT ’24 : Proceedings of the 14th International Conference on the Internet of Things (pp. 38–46). ACM. https://doi.org/10.1145/3703790.3703795
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  Projects: INTEND (2024–2026) / RapidREC (2023–2025)
• SLO-Aware Task Offloading Within Collaborative Vehicle Platoons / Sedlak, B., Morichetta, A., Wang, Y., Fei, Y., Wang, L., Dustdar, S., & Qu, X. (2025). SLO-Aware Task Offloading Within Collaborative Vehicle Platoons. In W. Gaaloul, M. Sheng, Q. Yu, & S. Yangui (Eds.), Service-Oriented Computing : 22nd International Conference, ICSOC 2024, Tunis, Tunisia, December 3–6, 2024, Proceedings, Part II (pp. 72–86). Springer Singapore. https://doi.org/10.1007/978-981-96-0808-9_6
  Projects: INTEND (2024–2026) / TEADAL (2022–2025)

2024

• Towards adaptive asynchronous federated learning for human activity recognition / Gajanin, R., Danilenka, A., Morichetta, A., & Nastic, S. (2024). Towards adaptive asynchronous federated learning for human activity recognition. arXiv. https://doi.org/10.34726/9720
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  Projects: INTEND (2024–2026) / RapidREC (2023–2025)
• RainCloud: Decentralized Coordination and Communication in Heterogeneous IoT Swarms / Loisel, F., Zeqo, G., Morichetta, A., Lackinger, A., & Dustdar, S. (2024). RainCloud: Decentralized Coordination and Communication in Heterogeneous IoT Swarms. arXiv. https://doi.org/10.34726/8680
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  Project: INTEND (2024–2026)
• INTEND: Human-Like Intelligence for Intent-Based Data Operations in the Cognitive Computing Continuum / Dautov, R., Song, H., Roman, D., Husom, E. J., Sen, S., Balionyte-Merle, V., Firmani, D., Leotta, F., Mathew, J. G., Rossi, J., Balzotti, L., Morichetta, A., Dustdar, S., Metsch, T., Frascolla, V., Khalid, A., Landi, G., Brenes, J., Toma, I., & Paulson, E. (2024). INTEND: Human-Like Intelligence for Intent-Based Data Operations in the Cognitive Computing Continuum. In A. Rula, E. Sallinger, O. Savkovic, I. Ciuciu, I. Toma, J. Xavier Parreira, R. Prodan, H. Song, & A. Soylu (Eds.), Companion Proceedings of the 8th International Joint Conference on Rules and Reasoning (RuleML+RR-Companion 2024). https://doi.org/10.34726/8579
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  Project: INTEND (2024–2026)
• Adaptive Stream Processing on Edge Devices through Active Inference / Sedlak, B., Casamayor Pujol, V., Morichetta, A., Donta, P. K., & Dustdar, S. (2024). Adaptive Stream Processing on Edge Devices through Active Inference. arXiv. https://doi.org/10.34726/8227
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  Projects: INTEND (2024–2026) / TEADAL (2022–2025)
• SLO-Aware Task Offloading within Collaborative Vehicle Platoons / Sedlak, B., Morichetta, A., Wang, Y., Fei, Y., Wang, L., Dustdar, S., & Qu, X. (2024). SLO-Aware Task Offloading within Collaborative Vehicle Platoons. arXiv. https://doi.org/10.34726/8228
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  Projects: INTEND (2024–2026) / TEADAL (2022–2025)
• Distributed AI in Zero-Touch Provisioning for Edge Networks: Challenges and Research Directions / Hazra, A., Morichetta, A., Murturi, I., Lovén, L., Dehury, C. K., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2024). Distributed AI in Zero-Touch Provisioning for Edge Networks: Challenges and Research Directions. Computer, 57(3), 69–78. https://doi.org/10.1109/MC.2023.3334913
• Distributed Model Serving for Real-time Opinion Detection / Pinter, P., Morichetta, A., & Dustdar, S. (2024). Distributed Model Serving for Real-time Opinion Detection. In 2024 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 64–73). IEEE. https://doi.org/10.1109/SOSE62363.2024.00014
  Project: INTEND (2024–2026)
• INTEND: Intent-Based Data Operation in the Computing Continuum / Firmani, D., Leotta, F., Mathew, J. G., Rossi, J., Balzotti, L., Song, H., Roman, D., Dautov, R., Husom, E. J., Sen, S., Balionyte-Merle, V., Morichetta, A., Dustdar, S., Metsch, T., Frascolla, V., Khalid, A., Landi, G., BRENES, J., Toma, I., … Paulson, E. (2024). INTEND: Intent-Based Data Operation in the Computing Continuum. In R. Matulevicius & H. Proper (Eds.), Proceedings of the Research Projects Exhibition Papers at the 36th International Conference on Advanced Information Systems Engineering (CAiSE 2024) (pp. 43–50). http://hdl.handle.net/20.500.12708/199889
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  Project: INTEND (2024–2026)
• RainCloud: Decentralized Coordination and Communication in Heterogeneous IoT Swarms / Loisel, F., Zeqo, G., Morichetta, A., Lackinger, A., & Dustdar, S. (2024). RainCloud: Decentralized Coordination and Communication in Heterogeneous IoT Swarms. In C. W. Tan & T. H. Teo (Eds.), Proceedings of The 1st International Symposium on Parallel Computing and Distributed Systems (pp. 186–195). IEEE. https://doi.org/10.1109/PCDS61776.2024.10743766
  Project: INTEND (2024–2026)
• Cohabitation of Intelligence and Systems: Towards Self-reference in Digital Anatomies / Morichetta, A., Lackinger, A., & Dustdar, S. (2024). Cohabitation of Intelligence and Systems: Towards Self-reference in Digital Anatomies. In 2024 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 102–110). IEEE. https://doi.org/10.1109/SOSE62363.2024.00018
  Project: INTEND (2024–2026)
• Time Series Predictions for Cloud Workloads: A Comprehensive Evaluation / Lackinger, A., Morichetta, A., & Dustdar, S. (2024). Time Series Predictions for Cloud Workloads: A Comprehensive Evaluation. In 2024 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 36–45). IEEE. https://doi.org/10.1109/SOSE62363.2024.00011
  Projects: AloTwin (2023–2025) / INTEND (2024–2026)

2023

• The Cohabitation of Intelligence and Systems: Examples and Future Scenarios / Morichetta, A. (2023, November 2). The Cohabitation of Intelligence and Systems: Examples and Future Scenarios [Presentation]. SmartData Seminar at Politecnico di Torino, Turin, Italy.
• Distributed Intelligence: The Next Leap for the Distributed Computing Continuum / Morichetta, A. (2023, October 23). Distributed Intelligence: The Next Leap for the Distributed Computing Continuum [Conference Presentation]. IEEE 9th World Forum on Internet of Things (WF-IoT 2023), Aveiro, Portugal.
• PolarisProfiler: A Novel Metadata-Based Profiling Approach for Optimizing Resource Management in the Edge-Cloud Continnum / Morichetta, A., Casamayor Pujol, V., Nastic, S., Dustdar, S., Vij, D., Xiong, Y., & Zhang, Z. (2023). PolarisProfiler: A Novel Metadata-Based Profiling Approach for Optimizing Resource Management in the Edge-Cloud Continnum. In 2023 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 27–36). IEEE. https://doi.org/10.1109/SOSE58276.2023.00010
• Intelligent Sampling: A Novel Approach to Optimize Workload Scheduling in Large-Scale Heterogeneous Computing Continuum / Casamayor Pujol, V., Morichetta, A., & Nastic, S. (2023). Intelligent Sampling: A Novel Approach to Optimize Workload Scheduling in Large-Scale Heterogeneous Computing Continuum. In Proceedings : 17th IEEE International Conference on Service-Oriented System Engineering (IEEE SOSE 2023) (pp. 140–149). IEEE. https://doi.org/10.1109/SOSE58276.2023.00024
• 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
• Edge Intelligence—Research Opportunities for Distributed Computing Continuum Systems / Casamayor Pujol, V., Donta, P. K., Morichetta, A., Murturi, I., & Dustdar, S. (2023). Edge Intelligence—Research Opportunities for Distributed Computing Continuum Systems. IEEE Internet Computing, 27(4), 53–74. https://doi.org/10.1109/MIC.2023.3284693
• Fundamental Research Challenges for Distributed Computing Continuum Systems / Casamayor Pujol, V., Morichetta, A., Murturi, I., Donta, P. K., & Dustdar, S. (2023). Fundamental Research Challenges for Distributed Computing Continuum Systems. Information, 14(3), Article 198. https://doi.org/10.3390/info14030198
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• Distributed Computing Continuum Systems – Opportunities and Research Challenges / Casamayor Pujol, V., Donta, P. K., Morichetta, A., Murturi, I., & Dustdar, S. (2023). Distributed Computing Continuum Systems – Opportunities and Research Challenges. In J. Troya, R. MIRANDOLA, E. Navarro, A. Delgado, S. Segura, G. Ortiz, C. Pautasso, C. Zirpins, P. Fernandez, & A. Ruiz-Cortes (Eds.), Service-Oriented Computing – ICSOC 2022 Workshops (pp. 405–407). Springer Cham. https://doi.org/10.1007/978-3-031-26507-5_41
• 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
• Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions / Hazra, A., Morichetta, A., Murturi, I., Loven, L., Dehury, C. K., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions. arXiv. https://doi.org/10.48550/arXiv.2311.17471
• FL-SERENADE: Federated Learning for SEmi-supeRvisEd Network Anomaly DEtection. A Case Study / Bekbulatova, V., Morichetta, A., & Dustdar, S. (2023). FL-SERENADE: Federated Learning for SEmi-supeRvisEd Network Anomaly DEtection. A Case Study. In 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 1072–1079). IEEE. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361504
• Learning-driven Zero Trust in Distributed Computing Continuum Systems / Murturi, I., Donta, P. K., Casamayor Pujol, V., Morichetta, A., & Dustdar, S. (2023). Learning-driven Zero Trust in Distributed Computing Continuum Systems. arXiv. https://doi.org/10.48550/arXiv.2311.17447
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Learning-Driven Zero Trust in Distributed Computing Continuum Systems / Murturi, I., Donta, P. K., Casamayor Pujol, V., Morichetta, A., & Dustdar, S. (2023). Learning-Driven Zero Trust in Distributed Computing Continuum Systems. In 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 0044–0049). IEEE. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361352
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)

2022

• BlinkRadar: Non-Intrusive Driver Eye-Blink Detection with UWB Radar / Hu, J., Jiang, H., Liu, D., Xiao, Z., Dustdar, S., Liu, J., Min, G., & Morichetta, A. (2022). BlinkRadar: Non-Intrusive Driver Eye-Blink Detection with UWB Radar. In Proceedings of the IEEE 42nd International Conference on Distributed Computing Systems (ICDCS 2022) (pp. 1040–1050). IEEE. https://doi.org/10.1109/ICDCS54860.2022.00104
• Cooperative Multiagent Deep Reinforcement Learning for Computation Offloading: A Mobile Network Operator Perspective / Li, K., Wang, X., He, Q., Yi, B., Morichetta, A., & Huang, M. (2022). Cooperative Multiagent Deep Reinforcement Learning for Computation Offloading: A Mobile Network Operator Perspective. IEEE Internet of Things Journal, 9(23), 24161–24173. https://doi.org/10.1109/JIOT.2022.3189445
• Exploring the Benefits of Blockchain Technology for MLOps Pipeline / Marcelletti, A., & Morichetta, A. (2022). Exploring the Benefits of Blockchain Technology for MLOps Pipeline [Conference Presentation]. 3rd International Workshop on Foundations of Consensus and Distributed Ledgers (FOCODILE 2022) at DisCoTec 2022, Lucca, Italy. http://hdl.handle.net/20.500.12708/81383
• High-Level Metrics for Service Level Objective-aware Autoscaling in Polaris: a Performance Evaluation / Bartelucci, N., Bellavista, P., Pusztai, T., Morichetta, A., & Dustdar, S. (2022). High-Level Metrics for Service Level Objective-aware Autoscaling in Polaris: a Performance Evaluation. In L. Mashayekhy, S. Schulte, V. Cardellini, B. Kantarci, Y. Simmhan, & B. Varghese (Eds.), 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC). IEEE. https://doi.org/10.1109/icfec54809.2022.00017
• 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)

2021

• A roadmap on learning and reasoning for distributed computing continuum ecosystems / Morichetta, A., Casamayor Pujol, V., & Dustdar, S. (2021). A roadmap on learning and reasoning for distributed computing continuum ecosystems. In 2021 IEEE International Conference on Edge Computing (EDGE). IEEE International Conference on Edge Computing (EDGE 2021), Guangzhou, China. IEEE. https://doi.org/10.1109/edge53862.2021.00021
• SLO Script: A Novel Language for Implementing Complex Cloud-Native Elasticity-Driven SLOs / Pusztai, T., Morichetta, A., Casamayor Pujol, V., Dustdar, S., Nastic, S., Ding, X., Vij, D., & Xiong, Y. (2021). SLO Script: A Novel Language for Implementing Complex Cloud-Native Elasticity-Driven SLOs. In C. K. Chang, E. Damiani, J. Fan, P. Ghodous, M. Maximilien, Z. Wang, R. Ward, & J. Zhang (Eds.), 2021 IEEE International Conference on Web Services (ICWS). IEEE. https://doi.org/10.1109/icws53863.2021.00017
• A Novel Middleware for Efficiently Implementing Complex Cloud-Native SLOs / Pusztai, T., Morichetta, A., Casamayor Pujol, V., Dustdar, S., Nastic, S., Ding, X., Vij, D., & Xiong, Y. (2021). A Novel Middleware for Efficiently Implementing Complex Cloud-Native SLOs. In C. A. Ardagna, C. K. Chang, E. Damiani, R. Ranjan, Z. Wang, R. Ward, J. Zhang, & W. Zhang (Eds.), 2021 IEEE 14th International Conference on Cloud Computing (CLOUD). IEEE. https://doi.org/10.1109/cloud53861.2021.00055
• Polaris Scheduler: Edge Sensitive and SLO Aware Workload Scheduling in Cloud-Edge-IoT Clusters / Nastic, S., Pusztai, T., Morichetta, A., Casamayor Pujol, V., Dustdar, S., Vij, D., & Xiong, Y. (2021). Polaris Scheduler: Edge Sensitive and SLO Aware Workload Scheduling in Cloud-Edge-IoT Clusters. In C. A. Ardagna, C. K. Chang, E. Damiani, R. Ranjan, Z. Wang, R. Ward, J. Zhang, & W. Zhang (Eds.), 2021 IEEE 14th International Conference on Cloud Computing (CLOUD). IEEE. https://doi.org/10.1109/cloud53861.2021.00034
• Understanding web pornography usage from traffic analysis / Morichetta, A., Trevisan, M., Vassio, L., & Krickl, J. (2021). Understanding web pornography usage from traffic analysis. Computer Networks, 189(107909), 107909. https://doi.org/10.1016/j.comnet.2021.107909
• Towards website domain name classification using graph based semi-supervised learning / Faroughi, A., Morichetta, A., Vassio, L., Figueiredo, F., Mellia, M., & Javidan, R. (2021). Towards website domain name classification using graph based semi-supervised learning. Computer Networks, 188(107865), 107865. https://doi.org/10.1016/j.comnet.2021.107865

2020

• SLOC: Service Level Objectives for Next Generation Cloud Computing / Nastic, S., Morichetta, A., Pusztai, T., Dustdar, S., Ding, X., Vij, D., & Xiong, Y. (2020). SLOC: Service Level Objectives for Next Generation Cloud Computing. IEEE Internet Computing, 24(3), 39–50. https://doi.org/10.1109/mic.2020.2987739

• Semi-supervised federated learning based intrusion detection in a heterogeneous Industrial IoT setting / Rieser, D. (2025). Semi-supervised federated learning based intrusion detection in a heterogeneous Industrial IoT setting [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.127971
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• Scheduling and Controlling Smart Micro Grids / Energy Communities as Kubernetes First-Class Citizens / Podlipnig, S. L. (2025). Scheduling and Controlling Smart Micro Grids / Energy Communities as Kubernetes First-Class Citizens [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.105563
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• Multi-agent systems in vehicular edge computing : a communication-centric approach to task handovers / Spring, N. (2024). Multi-agent systems in vehicular edge computing : a communication-centric approach to task handovers [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.115883
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• Navigating the transition from centralized to federated learning with non-IID data : a human activity recognition case study / Gajanin, R. (2024). Navigating the transition from centralized to federated learning with non-IID data : a human activity recognition case study [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.119725
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• Towards accurate Time series predictions for cloud workloads / Lackinger, A. (2023). Towards accurate Time series predictions for cloud workloads [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.115061
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• Decentralized task coordination in heterogeneous IoT clusters / Loisel, F. (2023). Decentralized task coordination in heterogeneous IoT clusters [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.105524
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• Decentralized communication in heterogeneous IoT clusters / Zeqo, G. (2023). Decentralized communication in heterogeneous IoT clusters [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.105525
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• Edge computing framework for the use case of steel saws in the steel industry / Reckendorfer, G. (2023). Edge computing framework for the use case of steel saws in the steel industry [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.99444
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• Stateful serverless computing: An evaluation of a new paradigm within cloud computing / Ettenauer, L. (2023). Stateful serverless computing: An evaluation of a new paradigm within cloud computing [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.103746
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• Reinforcement-learning-based, application-agnostic, and explainable auto-scaling in the cloud utilizing high-level SLOs / Mayerhofer, R. (2023). Reinforcement-learning-based, application-agnostic, and explainable auto-scaling in the cloud utilizing high-level SLOs [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.106505
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• From backend to frontend : Case study on adopting Mmcro frontends from a single page ERP application monolith / Kroiß, M. (2021). From backend to frontend : Case study on adopting Mmcro frontends from a single page ERP application monolith [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.85306
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