2 citations · 3 across the 4 of their papers we have counts for
4 papers
Reinforcement Learning-based Adaptive Path Selection for Programmable Networks
José Eduardo Zerna Torres, Marios Avgeris, Chrysa Papagianni +3
This work presents a proof-of-concept implementation of a distributed, in-network reinforcement learning (IN-RL) framework for adaptive path selection in programmable networks. By…
Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning
Cyril Shih-Huan Hsu, Anestis Dalgkitsis, Paola Grosso +1
In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective management of Virtualized Network Functi…
RAILS: Risk-Aware Iterated Local Search for Joint SLA Decomposition and Service Provider Management in Multi-Domain Networks
Cyril Shih-Huan Hsu, Chrysa Papagianni, Paola Grosso
The emergence of the fifth generation (5G) technology has transformed mobile networks into multi-service environments, necessitating efficient network slicing to meet diverse Servi…
Online SLA Decomposition: Enabling Real-Time Adaptation to Evolving Network Systems
Cyril Shih-Huan Hsu, Danny De Vleeschauwer, Chrysa Papagianni +1
When a network slice spans multiple technology domains, it is crucial for each domain to uphold the End-to-End (E2E) Service Level Agreement (SLA) associated with the slice. Conseq…