Network operation relies on heuristics to solve many tasks rapidly and efficiently across the protocol stack. These heuristics are the result of thorough human-driven design rooted in expert knowledge of the target system and problem. Recently, approaches powered by Artificial Intelligence have shown promising results in devising solutions that outperform long-established heuristics in classical problems. We explore the possibility of applying such Automated Heuristic Design (AHD) frameworks to network environments by (i) discussing the general integration of AHD with network operation and the associated challenges, as well as (ii) proposing a practical implementation of AHD for a specific networking task, i.e., 5G decoding. Initial results show how modern AHD tools can devise heuristics for Low-Density Parity Check decoding on par with state-of-the-art solutions implemented in production systems.

About Reza Namvar

Reza Namvar is a PhD Fellow at the Networks Data Science group in IMDEA Networks Institute under the supervision of Prof. Marco Fiore. His research investigates the applications of AI-based solutions for solving problems in the context of mobile networks. He graduated with a Master’s degree in Software Engineering from Shiraz University, where he researched cloud computing and federated learning for IoT applications under the supervision of Prof. Farshad Khunjush. He received his Bachelor’s degree in Computer Engineering from Azad University’s Shiraz Branch.

Este evento se impartirá en inglés