Mounir Bensalem

Mounir

Department of Electrical & Computer Engineering
Institut für Datentechnik und Kommunikationsnetze
Office: 11th floor, room 1105
Hans-Sommer-Str. 66
38106 Braunschweig

Email: mounir.bensalem@tu-bs.de

Biography

I am a Ph.D. student/ research assistant at the Institute of Computer and Network Engineering at the Technical University of Braunschweig, Germany. I obtained both my Engineering Diploma in Industrial Engineering  and my master degree in Information System Techniques from the National Engineering School of Tunis, Tunisia, in 2017. 

My main research interests revolve around the application of machine learning to a variety of networking problems, such as: Detection and Prevention of Jamming Attacks in Optical Networks, DNN Placement and Inference Serving in Edge Computing, Deep Learning for THz Channel Estimation.

Publications

Conferences and Workshops

  • M. Bensalem, E. Ipek and A. Jukan, "Scaling Serverless Functions in Edge Networks: A Reinforcement Learning Approach",  [arxiv]

  • M. Bensalem, F. Carpio and A. Jukan, "Towards optimal serverless function scaling in edge computing network." 2023 IEEE International Conference on Communications (ICC): Communication QoS, Reliability and Modeling (CQRM) Symposium,  Rome, Italy 2023, [arxiv]

  • M. Bensalem, A. Engelmann, A. Jukan, "Towards Optimal Path Allocation for Unreliable Reconfigurable Intelligent Surfaces," 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN), Vilanova i la Geltru, Spain, 2023, pp. 1-8, doi: 10.1109/DRCN57075.2023.10108214.  [arXiv]

  • M. Bensalem, J. Dizdarević and A. Jukan, "Benchmarking Various ML Solutions in Complex Intent-Based Network Management Systems," 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO), 2022, pp. 476-481, doi: 10.23919/MIPRO55190.2022.9803584.

  • C. V. Phung, M. Bensalem and A. Jukan, "Benchmarking Buffer Size in IoT Devices Deploying REST HTTP," 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO), 2022, pp. 409-414, doi: 10.23919/MIPRO55190.2022.9803729.  Best Paper Award 

  • M. Bensalem and A. Jukan, "Benchmarking Machine Learning Techniques for THz Channel Estimation Problems," 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO), 2022, pp. 459-464, doi: 10.23919/MIPRO55190.2022.9803741.

  • M. Bensalem,  J. Dizdarević, F. Carpio and A. Jukan, "The Role of Intent-Based Networking in ICT Supply Chains", accepted in 2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR). [arXiv]

  • Í. Brasileiro, M. Bensalem, A. Drummond, A. Jukan, "Jamming-Aware Control Plane in Elastic Optical Networks." arXiv preprint arXiv:2006.02896 (2020). [arxiv]

  • M. Bensalem,  J. Dizdarević, A. Jukan, "DNN Placement and Inference in Edge Computing", 43nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, 2020

  • M. Bensalem, Í. Brasileiro, A. Drummond, A. Jukan, "Embedding Jamming Attacks into Physical Layer Models in Optical Networks",2020 International Conference on Optical Network Design and Modeling (ONDM). [arxiv]

  • M. Bensalem,  J. Dizdarević, A. Jukan, "Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing." IEEE ICC 2020 Workshop - Edge Machine Learning for 5G Mobile Networks and Beyond, Dublin, Ireland, 2020.  [arxiv]

  • M. Bensalem, S. K. Singh, A. Jukan,, "On Detecting and Preventing Jamming Attacks with Machine Learning in Optical Networks", 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, USA, 2019. DOI: 10.1109/GLOBECOM38437.2019.9013238. [arxiv]
  • Dizdarević J., Carpio F., Bensalem M., Jukan A. (2019) Enhancing Service Management Systems with Machine Learning in Fog-to-Cloud Networks. In: Mencagli G. et al. (eds) Euro-Par 2018: Parallel Processing Workshops. Euro-Par 2018. Lecture Notes in Computer Science, vol 11339. Springer, Cham. DOI: 10.1007/978-3-030-10549-5_23