Mahdi Dibaei Asl

Mahdi Dibaei Asl, M. Sc.

Department of Computer Science
Chair of Computer Science 7 (Computer Networks and Communication Systems)

Room: Room 06.132
Martensstr. 3
91058 Erlangen

Short Biography

Mahdi Dibaei is a research assistant and part of the “Quality-of-Service” group at the Chair of Computer Networks and Communication Systems. He received his Bachelor of Science (B.Sc.) in 2006 in Compute Engineering – Software and his Master of Science (M.Sc.) in Computer Engineering – Computer Systems Architecture in 2014 focusing on “Implementing a Trust-based method in Wireless Sensor Networks”. His previous research was related to wireless networks with trust management, deep learning, and blockchain solutions. Currently, Mahdi is researching fault tree analysis and minimal cut sets as part of his doctorate.

More Information

Publikationen

2024

2021

2020

2019

2017

Projekte

  • MBPLE4Mobility - Continuous model-based product line development for control systems in vehicle technology

    (Third Party Funds Single)

    Term: 2021-07-01 - 2024-06-30
    Funding source: Bundesministerium für Wirtschaft und Technologie (BMWi)

    As part of a large consortium, the Chair of Computer Science 7 is involved in the project with the model-based system design of the vehicle communication systems under inclusion of variant diversity. For this purpose, on the one hand, an optimization for the configuration and resource design of the network architecture for different communication protocols and mechanisms is realized. On the other hand, safety analyses are performed using fault trees and extending them for product lines.

    Network calculus is used for the formal verification of the required real-time properties. Therefore, suitable approaches for the scheduling methods applied in the networking technologies (e.g. TAS, priority-based, CBS, etc.) have to be formulated.

    Model and code generators will be developed for automated and accelerated generation of the network optimizations. safety and real-time analyses. The results of these analyses are fed back into the modeling of the overall system.