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Research scientist

+43 1 58801 18491

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Short CV

Murturi is currently a researcher with the Distributed Systems Group, TU Wien, Vienna. He received his B.Sc. and M.Sc. degrees in Computer Engineering from the Faculty of Electrical and Computer Engineering, University of Prishtina, Kosova. He received his Ph.D. from the Technical University of Vienna (TU Wien) in 2022, under the supervision of Univ.Prof. Dr. Schahram Dustdar. His Ph.D. dissertation was titled “Resource Management and Elasticity Control in Edge Networks”. Previously, he worked as University Assistant at TU Wien and the University of Prishtina. His current research interests include the Internet of Things, Edge Computing, EdgeAI, and privacy in distributed, self-adaptive and cyber-physical systems. He joined the Distributed Systems Group in 2018.

Research Interests

Guest Editor (Call for papers)

Special issue on Learning-driven Ubiquitous Mobile Edge Computing: Network Management Challenges for Future Generation IoT (International Journal of Network Management, Wiley).

Submission Deadline: January 31, 2023 – More details



Thesis & Project Supervision

If you are interested in a topic that fits my research interests, I can (co-)advise your master theses. Furthermore, I can offer that we elaborate a topic together, based on your specific interests.

Co-Supervised Theses


  1. Murturi, I., & Dustdar, S. (2022). DECENT: A Decentralized Configurator for Controlling Elasticity in Dynamic Edge Networks. ACM Transactions on Internet Technology (TOIT).
  2. Murturi, I., Egyed, A., & Dustdar, S. (2022). Utilizing AI Planning on the Edge. IEEE Internet Computing, 26(2), 28–35. https://doi.org/10.1109/MIC.2021.3073434
  3. Boris, S., Murturi, I., & Dustdar, S. (2022). Specification and Operation of Privacy Models for Data Streams on the Edge. In 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC) (pp. 1–6). IEEE.
  4. Murturi, I., Jia, C., Kerbl, B., Wimmer, M., Dustdar, S., & Tsigkanos, C. (2021). On Provisioning Procedural Geometry Workloads on Edge Architectures. In 17th International Conference on Web Information Systems and Technologies (WEBIST) (pp. 1–6). Accepted.
  5. Murturi, I., & Dustdar, S. (2021). A Decentralized Approach for Resource Discovery using Metadata Replication in Edge Networks. IEEE Transactions on Services Computing.
  6. Dustdar, S., & Murturi, I. (2021). Towards IoT Processes on the Edge. In Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future (pp. 167–178). Springer.
  7. Murturi, I. (2021). Transforming the Method of Least Squares to the Dataflow Paradigm. In Handbook of Research on Methodologies and Applications of Supercomputing (pp. 114–121). IGI Global.
  8. Dustdar, S., & Murturi, I. (2020). Towards Distributed Edge-based Systems. In 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI) (pp. 1–9). IEEE.
  9. Murturi, I., Barzegaran, M., & Dustdar, S. (2020). A Decentralized Approach for Determining Configurator Placement in Dynamic Edge Networks. In IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) (pp. 1–10). IEEE.
  10. Dustdar, S., & Murturi, I. (2020). Towards Distributed Edge-based Systems. In IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) (pp. 1–9). IEEE.
  11. Alkhabbas, F., Murturi, I., Spalazzese, R., Davidsson, P., & Dustdar, S. (2020). A Goal-driven Approach for Deploying Self-adaptive IoT Systems. In IEEE International Conference on Software Architecture (ICSA 2020) (pp. 1–11). IEEE.
  12. Avasalcai, C., Murturi, I., & Dustdar, S. (2020). Edge and Fog: A Survey, Use Cases, and Future Challenges. Fog Computing: Theory and Practice.
  13. Arleo, A., Tsigkanos, C., Jia, C., Leite, R. A., Murturi, I., Klaffenboeck, M., … Sorger, J. (2019). Sabrina: Modeling and Visualization of Economy Data with Incremental Domain Knowledge. ArXiv Preprint ArXiv:1908.07479.
  14. Murturi, I., Avasalcai, C., Tsigkanos, C., & Dustdar, S. (2019). Edge-to-Edge Resource Discovery using Metadata Replication. In 2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC) (pp. 1–6). IEEE.
  15. Tsigkanos, C., Murturi, I., & Dustdar, S. (2019). Dependable Resource Coordination on the Edge at Runtime. In Proceedings of the IEEE, 2019 (pp. 1–17).
  16. Dustdar, S., Avasalcai, C., & Murturi, I. (2019). Edge and Fog Computing: Vision and Research Challenges. In 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 96–9609). IEEE.
  17. Rexha, B., & Murturi, I. (2019). Applying efficient crowdsourcing techniques for increasing quality and transparency of election processes. Electronic Government, an International Journal, 15(1), 107–128.
  18. Bajrami, X., & Murturi, I. (2018). An efficient approach to monitoring environmental conditions using a wireless sensor network and NodeMCU. Elektrotechnik Und Informationstechnik, 135(3), 294–301.

Academic Activities

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