M.Sc. Ilir Murturi

University Assistant

imurturi@dsg.tuwien.ac.at

+43 1 58801 18491

last edited: 18.09.2019

Short CV

Murturi is a university assistant and PhD student at the Distributed Systems Group of the Institute of Information Systems Engineering. After receiving his bachelor’s degree in 2011, he started working as an intern in Robert Bosch GmbH, at the Division of Electrical Vehicles and Hybrid Systems, Germany. In 2015, he received his master’s degree in Computer Engineering at University of Prishtina where he continued his career as a university assistant. In 2018, he joined the Distributed Systems Group.

Research Interests

• Edge Computing
• Internet of Things (IoT)
• Resource Provisioning

Teaching

Courses

• 184.269 Advanced Internet Computing VU, 3.0 ECTS
• 184.194 Seminar in Distributed Systems SE, 3.0 ECTS
• 194.058 Project in Computer Science 1 PR, 6.0 ECTS
• 194.059 Project in Computer Science 2 PR, 6.0 ECTS

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.

Publications

1. 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.
2. 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.
3. Tsigkanos, C., Murturi, I., & Dustdar, S. (2019). Dependable Resource Coordination on the Edge at Runtime. In Proceedings of the IEEE, 2019 (pp. 1–17).
4. 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.
5. 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.
6. 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

I have been an official reviewer for:

• IEEE Internet Computing external link