8 citations · 15 across the 5 of their papers we have counts for
10 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…
On the Robustness of Controlled Deep Reinforcement Learning for Slice Placement
Jose Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
The evaluation of the impact of using Machine Learning in the management of softwarized networks is considered in multiple research works. Beyond that, we propose to evaluate the r…
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…
A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement
Jose Jurandir Alves Esteves, Amina Boubendir, Fabrice Guillemin +1
Network Slice placement with the problem of allocation of resources from a virtualized substrate network is an optimization problem which can be formulated as a multiobjective Inte…
Scheduling Bag-of-Tasks in Clouds using Spot and Burstable Virtual Machines
Luan Teylo, Luciana Arantes, Pierre Sens +1
Leading Cloud providers offer several types of Virtual Machines (VMs) in diverse contract models, with different guarantees in terms of availability and reliability. Among them, th…