Apr 22, 2022 · We propose, in this paper, a new method that dynamically computes the optimal number of controllers, determines their optimal locations, and at the same time ...

In this context, we propose, in this paper, a new method that dynamically computes the optimal number of controllers, determines their optimal locations, and at ...

Jul 22, 2024 · Second, we propose a simple yet computationally efficient heuristic, called Deep Q-Network based Dynamic Clustering and Placement (DDCP), that ...

Mar 15, 2022 · In this paper, a new method that dynamically computes the optimal number of controllers, determines their optimal locations, and at the same ...

Second, we propose a simple yet computationally efficient heuristic, called Deep Q-Network based Dynamic Clustering and Placement (DDCP), that leverages the ...

Dynamic clustering of software defined network switches and controller placement using deep reinforcement learning ; El Hocine Bouzidi · PersonId : 1365364; ORCID ...

The contributions of this paper are: it improves exiting dynamic controller placement studies by considering the discrepancy of network states before and after ...

A Deep Q-Network (DQN) empowered Dynamic flow Data Driven approach for Controller Placement Problem (D4CPP), which integrates the historical network data ...

Oct 22, 2024 · This paper proposes a novel deep reinforcement learning-based model that dynamically and strategically adjusts the location of the controller to ...

Mar 22, 2022 · Dynamic clustering of software defined network switches and controller placement using deep reinforcement learning ; Professeur. Langar, Rami.