5 papers
DRL-based Slice Placement under Realistic Network Load Conditions
José Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
We propose to demonstrate a network slice placement optimization solution based on Deep Reinforcement Learning (DRL), referred to as Heuristically-controlled DRL, which uses a heur…
DRL-based Slice Placement Under Non-Stationary Conditions
Jose Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
We consider online learning for optimal network slice placement under the assumption that slice requests arrive according to a non-stationary Poisson process. We propose a framewor…
Controlled Deep Reinforcement Learning for Optimized Slice Placement
Jose Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
We present a hybrid ML-heuristic approach that we name "Heuristically Assisted Deep Reinforcement Learning (HA-DRL)" to solve the problem of Network Slice Placement Optimization. T…
Edge-enabled Optimized Network Slicing in Large Scale Networks
Jose Jurandir Alves Esteves, Amina Boubendir, Fabice Guillemin +1
In this demo paper, we consider the network slice placement optimization problem and give some insights into a fast heuristic algorithm tailored to placement in large scale network…
Heuristic for Edge-enabled Network Slicing Optimization using the Power of Two Choices
Jose Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
We propose an online heuristic algorithm for the problem of network slice placement optimization. The solution is adapted to support placement on large scale networks and integrate…