Multi-constrained and edge-enabled selection of uav participants in federated learning process

HIGHLIGHTS

• who: Sofiane Dahmane et al. from the Laboratoire d'Informatique et de Mathématiques, Université Amar Telidji, Laghouat, AlgeriaDRIVE, University Bourgogne Franche-Comté, Nevers, France have published the paper: Multi-Constrained and Edge-Enabled Selection of UAV Participants in Federated Learning Process, in the Journal: Electronics 2022, 11, 2119. of /2022/
• what: The authors design a novel and S-MEC-enabled framework that optimizes the selection of UAV participants at each FL training round named FedSel. The authors show that the problem can be NP-hard and design a novel Tabu Search-based (TS) algorithm . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.